Repository: infer-actively/pymdp (language: python)

Issue:
Move plot functions from explicit definition in demos to `utils` module, change axes tick labels calls
will also make compatible with earlier versions of `matplotlib` and `seaborn`

see https://github.com/infer-actively/pymdp/pull/95 by @tverbele


Discussion / hints:

Fix patch:
diff --git a/docs/notebooks/tmaze_demo.ipynb b/docs/notebooks/tmaze_demo.ipynb
index 68644d6a..5f8c9e3d 100644
--- a/docs/notebooks/tmaze_demo.ipynb
+++ b/docs/notebooks/tmaze_demo.ipynb
@@ -48,11 +48,10 @@
     "import sys\n",
     "import pathlib\n",
     "import numpy as np\n",
-    "import seaborn as sns\n",
-    "import matplotlib.pyplot as plt\n",
     "import copy\n",
     "\n",
     "from pymdp.agent import Agent\n",
+    "from pymdp.utils import plot_beliefs, plot_likelihood\n",
     "from pymdp import utils\n",
     "from pymdp.envs import TMazeEnv"
    ]
@@ -66,27 +65,6 @@
     "Define some utility functions that will be helpful for plotting."
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def plot_beliefs(belief_dist, title=\"\"):\n",
-    "    plt.grid(zorder=0)\n",
-    "    plt.bar(range(belief_dist.shape[0]), belief_dist, color='r', zorder=3)\n",
-    "    plt.xticks(range(belief_dist.shape[0]))\n",
-    "    plt.title(title)\n",
-    "    plt.show()\n",
-    "    \n",
-    "def plot_likelihood(A, title=\"\"):\n",
-    "    ax = sns.heatmap(A, cmap=\"OrRd\", linewidth=2.5)\n",
-    "    plt.xticks(range(A.shape[1]))\n",
-    "    plt.yticks(range(A.shape[0]))\n",
-    "    plt.title(title)\n",
-    "    plt.show()"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -123,7 +101,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -139,7 +117,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -167,7 +145,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -179,12 +157,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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8H6YkNXJKLkmtrDAlqU2mV3sEyzIwJfXDc5iS1MjAlKRWLvpIUhsrTElq5NeKJKmVFaYktXFKLkmtnJJLUhsrTElqZWBKUhtXySWpkVNySWplYEpSGytMSWrlOUxJamOFKUmtrDAlqUmsMCWplYEpSW2sMCWplYEpSW38q5GS1MgpuSS1MjAlqY0VpiS1MjAlqY0VpiQ16nyVvO8LNyUdZbKCbUxPyblJbk0yl2TTIseT5PLh8ZuTPGNcnwampH4k7duy3WQauAI4D3gy8PIkT17Q7Dzg9OE2A/ztuOG1TcmPW9PU7Khw/CmrPYJubKpa7SH0w9+RCZnYOcwzgbmq2gmQ5BpgA7BjpM0G4N1VVcCNSU5KckpV3bZUp8sGZpJXVdXsQx/74S/JjJ/FgJ/FPn4WE3bcmubETDLDoDLca3bkv8VaYNfIsXngrAVdLNZmLbBkYI6bks+MOX408bPYx89iHz+LVVJVs1V1xsg2+g/XYsG7cErU0uZBPIcp6Ug0D5w6sr8O2H0AbR7EwJR0JNoGnJ7ktCTHAhcAWxa02QJcOFwtPxv4znLnL2H8oo/nZvbxs9jHz2IfP4sOVdWeJBuB64Bp4Kqq2p7kkuHxzcBW4HxgDrgXuHhcvylXOiWpiVNySWpkYEpSIwNTkhoZmJLUyMCUpEYGpiQ1MjAlqdH/A4QT18T3uc8oAAAAAElFTkSuQmCC",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -201,14 +179,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -225,14 +203,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "metadata": {
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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/I8nPzerTwJTUj6R9mdpNFoGtwOnAicDZSU6caHYOcGNV/TzwLuBtM0+vqqbtn7pTkgb2/wLkLde3Z84RR694vCRPAjZX1bPG668FqKq3DtpcPG7ztSSHAVcDx9aUULzLNcwkS8DSePXDVfVrzR9Ah4QkS1W17UCfh/oyl7+LKSG43PG4M6sAtg2Ovw7YO9i3Dzh1oos72lTVbUluAo4GrlvpmHcZklfVtqo6uapOBh7TevI6pCzNbqJD0D36dzHMqvGy5v+Jew1T0sHoKmDDYH39eNuybcZD8qOA66d1amBKOhjtBE5IcnySw4GzgO0TbbYDLxm//lXgi9OuX8Ls+zC9TqXl+Heh5XTzdzG+JrkJuBhYBC6sqkuTbAF2VdV24M+ADyXZA9zAKFSnmjVLLkkac0guSY0MTElqZGBKUiMDU5IaGZiS1MjAlKRGBqYkNfp/qCCU1iacnscAAAAASUVORK5CYII=",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -258,7 +236,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -276,14 +254,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 10,
    "metadata": {
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -318,14 +296,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -342,12 +320,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -364,12 +342,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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e04ApaThm1+fdChw18vxIYNsi69xVVfcD9ye5FvhxYMmAaZdc0mBk1armaYqNwLFJjklyAHAmsH5snY8DP51kvyQHAycAt0wq1AxT0mDMapS8qrYnOR+4GpgDLq6qm5Kc1y+/qKpuSfJJ4EbgEeB9VfXFSeUaMCUNxwxPXK+qDcCGsXkXjT3/XeB3W8s0YEoajmFf6GPAlDQc3q1IkhplzoApSW2GHS8NmJIGxC65JLUZeLw0YEoakIHfD9OAKWkwzDAlqdHQ77huwJQ0HAZMSWo08D65AVPSYAw8XhowJQ3IwCOmAVPSYGTgd+g1YEoajr1i0OfAw1e4Go8htsUC22KBbTETQ79b0Q4J8Oh/Ylu3bqn/LyRJK2B2/2Z3ReyQYY79J7bx/7ImSStn4BlmU5d87cB3YqWtrYXfDdvCtphnWywYbYtdslccw5Sk3WHV3J6uwUQGTEnDYYYpSY0GfiKmAVPScJhhSlKjgQ+eGTAlDccqu+SS1GbOUXJJamOXXJIaGTAlqZHHMCWpkRmmJLXxv0ZKUitHySWpkV1ySWrkoI8kNRp4hjnscC5p35K0T1OLyilJbk2yKckFE9Z7XpLvJjljWplmmJKGY0aDPknmgAuBk4GtwMYk66vq5kXWeydwdUu5ZpiShmN2/wTteGBTVW2uqoeAy4HTF1nvl4GPAl9vqt5y9kWSVlRWNU+j/+G2n9aMlLQa2DLyfGs/b+GlktXAPwMuaq2eXXJJw7GME9fH/sPtuMUKGv9Pbe8C3lRV3239f+gGTEnDMbtR8q3AUSPPjwS2ja3zXODyPlg+EXhJku1V9bGlCjVgShqO2Z2HuRE4NskxwJ3AmcArR1eoqmPmHye5BPjEpGAJBkxJQzKjgFlV25OcTzf6PQdcXFU3JTmvX9583HKUAVPScMzwv0ZW1QZgw9i8RQNlVZ3TUqYBU9JwDPtCHwOmpAEZ+KWRBkxJw2HAlKRGBkxJamTAlKRGBkxJamTAlKRGBkxJamXAlKQ2/ptdSWpkl1ySWhkwJamNGaYkNTJgSlKjYcdLA6akAZnh/TBXggFT0nDYJZekRgZMSWo07HhpwJQ0IGaYktTIQR9JamSGKUmNBh4wh53/StKAmGFKGo6BZ5ipqknLJy6UpBG7HO0e+eLFzTFn1Y+9ZrdH1x265EnWJLkhyQ3r1q3b3fWRtC/LqvZpD9ihS15V64D5SGmGKWn3GXiXvO0Y5oN3r3A1Bu7Awxce2xYLj22Lhce2xWzK8TxMSWq1N2SYkrQ77BVdcknaHeySS1IjA6YktRp2wBx27STtW5L2aWpROSXJrUk2JblgkeVnJbmxn65L8uPTyjTDlDQcMxr0STIHXAicDGwFNiZZX1U3j6x2O/AzVXVPklPpzj8/YVK5ZpiSBiTLmCY6HthUVZur6iHgcuD00RWq6rqquqd/ej1w5LRCDZiShmPVXPM0ehl3P60ZKWk1sGXk+dZ+3lJ+CfiTadWzSy5pQNq75GOXcbcUtOil3kmeTxcwf2raaxowJQ3H7E4r2gocNfL8SGDbDi+X/EPgfcCpVTX1+la75JIGI0nzNMVG4NgkxyQ5ADgTWD/2Wk8BrgReVVW3tdTPDFPSgMxmlLyqtic5H7gamAMurqqbkpzXL78I+C3gcOA9fQDeXlXPnVi7phsIeyeWhce2xcJj22LhsW0BM4h29eVPNt9SMkefstsvPDfDlDQcXhopSY0MmJLUytu7SVIb74cpSY3skktSKzNMSWqTuT1dg4kMmJKGw2OYktTIgClJrRz0kaQ2ZpiS1MjTiiSplRmmJLWxSy5JreySS1IbM0xJamXAlKQ2jpJLUiO75JLUyoApSW3MMCWplccwJamNGaYktTLDlKQmMcOUpFYGTElqY4YpSa0MmJLUxv8aKUmN7JJLUisDpiS1McOUpFYGTElqY4YpSY0GPko+7As3Je1jsoxpSknJKUluTbIpyQWLLE+Sd/fLb0zy7GllGjAlDUfSPk0sJnPAhcCpwHHAK5IcN7baqcCx/bQG+MNp1Wvrkh94eNNq+wTbYoFtscC2mJGZHcM8HthUVZsBklwOnA7cPLLO6cClVVXA9UkOS/LkqvrKUoVODJhJXldV63a97o99SdbYFh3bYoFtMWMHHt4cMZOsocsM560beS9WA1tGlm0FThgrYrF1VgNLBsxpXfI1U5bvS2yLBbbFAttiD6mqdVX13JFp9IdrscBbY89b1nkUj2FK2httBY4aeX4ksG0n1nkUA6akvdFG4NgkxyQ5ADgTWD+2znrg7H60/ETgbycdv4Tpgz4em1lgWyywLRbYFgNUVduTnA9cDcwBF1fVTUnO65dfBGwAXgJsAr4NnDut3HQDRJKkaeySS1IjA6YkNTJgSlIjA6YkNTJgSlIjA6YkNTJgSlKj/w+C0uOArzWQqgAAAABJRU5ErkJggg==",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -386,12 +364,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -420,7 +398,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -462,7 +440,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -478,7 +456,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -494,14 +472,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 18,
    "metadata": {
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -518,14 +496,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 19,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -549,7 +527,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -567,12 +545,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -600,7 +578,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -610,12 +588,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -640,7 +618,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 24,
    "metadata": {
     "scrolled": false
    },
@@ -650,17 +628,17 @@
      "output_type": "stream",
      "text": [
       " === Starting experiment === \n",
-      " Reward condition: Left, Observation: [CENTER, No reward, Cue Right]\n",
+      " Reward condition: Right, Observation: [CENTER, No reward, Cue Right]\n",
       "[Step 0] Action: [Move to CUE LOCATION]\n",
-      "[Step 0] Observation: [CUE LOCATION,  No reward, Cue Left]\n",
-      "[Step 1] Action: [Move to LEFT ARM]\n",
-      "[Step 1] Observation: [LEFT ARM,  Reward!, Cue Left]\n",
-      "[Step 2] Action: [Move to LEFT ARM]\n",
-      "[Step 2] Observation: [LEFT ARM,  Reward!, Cue Left]\n",
-      "[Step 3] Action: [Move to LEFT ARM]\n",
-      "[Step 3] Observation: [LEFT ARM,  Reward!, Cue Right]\n",
-      "[Step 4] Action: [Move to LEFT ARM]\n",
-      "[Step 4] Observation: [LEFT ARM,  Reward!, Cue Left]\n"
+      "[Step 0] Observation: [CUE LOCATION,  No reward, Cue Right]\n",
+      "[Step 1] Action: [Move to RIGHT ARM]\n",
+      "[Step 1] Observation: [RIGHT ARM,  Reward!, Cue Right]\n",
+      "[Step 2] Action: [Move to RIGHT ARM]\n",
+      "[Step 2] Observation: [RIGHT ARM,  Reward!, Cue Left]\n",
+      "[Step 3] Action: [Move to RIGHT ARM]\n",
+      "[Step 3] Observation: [RIGHT ARM,  Reward!, Cue Left]\n",
+      "[Step 4] Action: [Move to RIGHT ARM]\n",
+      "[Step 4] Observation: [RIGHT ARM,  Reward!, Cue Left]\n"
      ]
     }
    ],
@@ -709,14 +687,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 25,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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z1GWfTOmjcBslGA+hHPs/Y0NHpnHLgRvq87Tx4aD02Jzy2J3ACbXcV1DO8dMnKe8NlJvfY+p6vhN4aWZeP9Fnpuk0YNeIeFmfcUdTri3jvajPpNwsDeKblF7oP4uI8bIupPREHdRrKZ1y1lKeL783M78xjc8DvLOeZzdSOi59n9JD9o7JPzahaZ2/mfklyjF1Vr2GXgwcOOCy+m3Dfv6OclM4/vokZb+eTrk2XUG5Tr25lulqyqOOYyjb5QI29Av5I+Av6rq9hw0tmWTmncD7KV+dujkiuv1zNvVYfTilT8StlKb55ZTeyROK7Nu3RpI2bxHxQeDhmfmGjfz8OZQOfZdNObE0BcNW0qxQm463pLSePIPSTPimzPzyTJZLgs3wt5ElaQLbUJ7b3kFpTjyJ8mt0mgERcVpEXBsRF08wPiLi5IhYFREXRcTTHugyPpCs2UqShi4inkfpW/KZzHxin/EHUZ7LHkR5jvzRzNzY/iAjz5qtJGnoMvNbTP794IMpQZxZfixou4jo9zsLs4I/PD2CImIRsAjg1FNP3XvRokUzXCJJm4mYepKJHR8xcFPnCeXXproXpyWZuWQai5vP/X9QY019b7JfV9tsGbYjqB6w4wet7fySHhDTaersuU5tjH43BrP2emfYbibuPenQqSeaxcaOWf81Z7eF22K97rY4PjapUrfZO34I/W8e4C24hvv/ytcC6i8BzkY+s5UkASUQBn0NwVLg9bVX8jOBW3Lyf9CxWbNmK0kChlv7iogzKb/TvVNErKH8lOoWAJm5mPI96IMov/x2J+VfR85ahq0kCSj/mHVYMvO1U4xP4I+HuMiRZthKkoAH/JntrxXDVpIE2ImnJcNWkgQYti0ZtpIkwGbklgxbSRJgzbYlw1aSBAy3N7Luz7CVJAHWbFsybCVJgM9sWzJsJUmANduWDFtJEmDYtmTYSpIAO0i1ZNhKkgBrti0ZtpIkwA5SLRm2kiTAmm1Lhq0kCTBsWzJsJUmAzcgtGbaSJMDeyC0ZtpIkwGbklgxbSRJg2LZk2EqSAJ/ZtmTYSpIAa7YtGbaSJMCwbcmwlSQBMGeODcmtGLaSJAAiDNtWDFtJEmDNtiXDVpIEWLNtybCVJAEQ1mybMWwlSQDMGbM/ciuGrSQJsBm5JcNWkgTYjNySYStJAqzZtmTYSpIAv/rTkmErSQKs2bZk2EqSAHsjt2TYSpIAO0i15G2MJAkozciDvgac3wERsTIiVkXEcX3GbxsR/xwRF0bEJRFxxNBXakRYs5UkAcOt2UbEGHAK8CJgDbAiIpZm5qWdyf4YuDQzXxYRDwNWRsQ/ZObdQyvIiLBmK0kChl6z3QdYlZmX1/A8Czi4Z5oEtokyw4cANwLrhrlOo8KarSQJmN5XfyJiEbCo89aSzFzSGZ4PrO4MrwH27ZnNx4ClwFpgG+A1mXnfdMq8uTBsJUnA9Hoj12BdMskk/ZI7e4ZfDFwA/DbwKOAbEfHtzLx14IJsJmxGliQBQ29GXgMs7AwvoNRgu44AvpjFKuAK4HFDWZkRY9hKkgCIOYO/BrAC2CMido+ILYFDKE3GXVcDLwCIiJ2BxwKXD2+NRofNyJIkYLi/IJWZ6yLiaOBsYAw4LTMviYij6vjFwF8Cn4qIH1CanY/NzOuHVogRYthKkoDh/6hFZi4DlvW8t7jz91rgd4a60BFl2EqSABjz5xqbMWwlSYD/iKAlw1aSBPjbyC0ZtpIkwJptS4atJAmwZtuSYStJAqzZtmTYSpIAmDN3bKaLMGsZtpKkwpptM4atJAnwmW1Lhq0kCYCY449atGLYSpIAO0i1ZNhKkgqbkZsxbCVJAMwZszdyK4atJAmwg1RLhq0kqTBsmzFsJUkARNgbuRXDVpIE2IzckmErSQIg7CDVjGErSQKs2bZk2EqSAMO2JcNWkgT4C1ItGbaSpMLfRm7GsJUkATYjt2TYSpIAf66xJcNWkgRYs23JsJUkFXaQasawlSQB1mxbMmwlSQCEvZGbMWwlSYDfs23JsJUkARBz7Y3cimErSQKs2bZk2EqSADtItWTYSpIKa7bNGLaSJMCabUv285YkFXNi8NcAIuKAiFgZEasi4rgJptk/Ii6IiEsiYvlQ12eEWLOVJAHDbUWOiDHgFOBFwBpgRUQszcxLO9NsB3wcOCAzr46I3xheCUaLNVtJUjHcmu0+wKrMvDwz7wbOAg7umeZQ4IuZeTVAZl471PUZIYatJAkoNdvBX7EoIs7vvBb1zG4+sLozvKa+1/UYYPuIODcivh8Rr2+5fjPJZmRJUjGNduTMXAIsmWxu/T7WMzwX2Bt4ATAP+G5EfC8zfzRwQTYThq0kqRhuW+caYGFneAGwts8012fmHcAdEfEt4CnArAtbm5ElSUD5RwSDvgawAtgjInaPiC2BQ4ClPdN8BXhuRMyNiK2BfYHLhrpSI8KarSQJGG5v5MxcFxFHA2cDY8BpmXlJRBxVxy/OzMsi4l+Ai4D7gE9k5sXDK8XoMGwlScWQf9QiM5cBy3reW9wz/GHgw0Nd8AgybCVJhT8g1YxhK0kC/K8/LRm2kiQAYsywbcWwlSQVZm0zhq0kqbAZuRnDVpIEmLUtGbaSpML/Z9uMYStJAqzZtmTYSpIACGu2zRi2kqTCsG3GsJUkFbYjN2PYSpIAs7Ylw1aSVJi2zRi2kiQAwv9w3oxhK0kq7CDVTGTmTJdBk3MHSRrUJqXlvScdOvD1ZuyYM0zmabDRYARFxKKIOD8izl+yZMlMF0fSr4s5MfhL02Iz8gjKzCXAeMpas5X0wLCDVDOG7Wbi3pMOnekizKixY85Y/7fbwm0xrrstuOuGmSvIKNhqx02fhzXWZgxbSVIxZ2ymSzBrGbaSpMKabTOGrSSp8Iu2zRi2kqTCmm0zhq0kqbA3cjOGrSSpmGMzciuGrSSpGLM3ciuGrSSpsBm5GcNWklQYts0YtpKkwme2zRi2kqTCmm0zhq0kCYDwe7bNGLaSpMLeyM0YtpKkwmbkZgxbSVJhB6lmDFtJUmHNthlvYyRJRcTgr4FmFwdExMqIWBURx00y3TMi4t6IeOXQ1mXEWLOVJBVD7CAVEWPAKcCLgDXAiohYmpmX9pnug8DZQ1v4CLJmK0kq5sTgr6ntA6zKzMsz827gLODgPtO9GfgCcO3wVmT0GLaSpCLmDPyKiEURcX7ntahnbvOB1Z3hNfW9DYuLmA/8LrC47YrNPJuRJUnFNH7UIjOXAEsmmaTfzLJn+G+AYzPz3pjlnbMMW0lSMdzAWwMs7AwvANb2TPN04KwatDsBB0XEusz88jALMgoMW0lSMdzv2a4A9oiI3YGfAocAh3YnyMzdx/+OiE8BX52NQQuGrSRp3BDDNjPXRcTRlF7GY8BpmXlJRBxVx8/657Rdhq0kqYjh9pnNzGXAsp73+oZsZh4+1IWPGMNWklTM7j5KM8qwlSQVs7xH8EwybCVJhWHbjGErSSoM22YMW0lSYdg2Y9hKkgrDthnDVpJUGLbNGLaSpMKwbcawlSRVhm0rhq0kqZjGf/3R9Bi2kqTCZuRmDFtJUmXYtmLYSpIKa7bNGLaSpMKwbcawlSQVZm0zhq0kqRjy/7PVBoatJKmwGbkZw1aSVBi2zRi2kqTCrG3GsJUkFdZsmzFsJUmFHaSaMWwlSYU122YMW0lSYdg2Y5uBJEmNWbOVJBXWbJsxbCVJhWHbjGErSSrsjdyMYStJKqzZNmPYSpIKa7bNGLaSpMqabSuGrSSpsBm5GcNWklTYjNyMYStJKgzbZgxbSVJl2LbilpUkFRGDvwaaXRwQESsjYlVEHNdn/GERcVF9nRcRTxn6Oo0Ia7aSpGKIHaQiYgw4BXgRsAZYERFLM/PSzmRXAPtl5k0RcSCwBNh3aIUYIdZsJUlVTOM1pX2AVZl5eWbeDZwFHNydIDPPy8yb6uD3gAVDWImRZNhKkoo5YwO/ImJRRJzfeS3qmdt8YHVneE19byJ/AHx92Ks0KmxGliRVgzcjZ+YSSrPvdGaWfSeMeD4lbJ8zcAE2M4atJKkY7ld/1gALO8MLgLW/ssiIJwOfAA7MzBuGWYBRYjOyJAmAiBj4NYAVwB4RsXtEbAkcAiztWd6uwBeB12Xmj4a+QiPEmq0kqRpeb+TMXBcRRwNnA2PAaZl5SUQcVccvBt4D7Ah8vAb4usx8+tAKMUIMW0lSMeRfkMrMZcCynvcWd/5+E/CmoS50RBm2kqTCn2tsxrCVJBWGbTOGrSSp8l/stWLYSpIK/59tM4atJKmwGbkZw1aSVFmzbcWwlSQVMTbTJZi1DFtJUuEz22YMW0lSYdg2Y9hKkio7SLVi2EqSCmu2zRi2kqTCr/40Y9hKkiprtq0YtpKkwmbkZgxbSVJlM3Irhq0kqbBm24xhK0mqDNtWDFtJUmFv5GYMW0lSYTNyM4atJKkybFsxbCVJhTXbZgxbSVLlM9tWDFtJUmHNthnDVpJUWbNtxbCVJAEQ1mybMWwlSZVh24phK0kqrNk2Y9hKkirDthXDVpJUxNhMl2DWMmwlSYXNyM0YtpKkyrBtxbCVJBXWbJsxbCVJlWHbimErSSqs2TZj2EqSCnsjN+MPYUqSqpjGa4C5RRwQESsjYlVEHNdnfETEyXX8RRHxtCGtyMgxbCVJRcTgrylnFWPAKcCBwJ7AayNiz57JDgT2qK9FwN8Nd4VGR2TmTJdBk3MHSRrUpj10veuGwa83W+046bIi4lnA8Zn54jr8LoDMPLEzzanAuZl5Zh1eCeyfmddMv/CjzWe2Iy4ijszMJTNdjlEQEYvcFoXbYgO3xRBNEaBdEbGIUhsdt6RnP8wHVneG1wD79sym3zTzgVkXtjYjj75FU0/ya8NtsYHbYgO3xQzIzCWZ+fTOq/eGp19w99acB5lmVjBsJUktrAEWdoYXAGs3YppZwbCVJLWwAtgjInaPiC2BQ4ClPdMsBV5feyU/E7hlNj6vBZ/Zbg58FrWB22IDt8UGbosRlJnrIuJo4GxgDDgtMy+JiKPq+MXAMuAgYBVwJ3DETJW3NXsjS5LUmM3IkiQ1ZthKktSYYStJUmOGrSRJjRm2kiQ1ZthKktSYYStJUmP/H8vIhnVke8SvAAAAAElFTkSuQmCC",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -733,12 +711,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -769,12 +747,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -792,7 +770,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3.7.10 ('pymdp_env')",
+   "display_name": "Python 3.8.8 ('base')",
    "language": "python",
    "name": "python3"
   },
@@ -806,11 +784,11 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.10"
+   "version": "3.8.8"
   },
   "vscode": {
    "interpreter": {
-    "hash": "43ee964e2ad3601b7244370fb08e7f23a81bd2f0e3c87ee41227da88c57ff102"
+    "hash": "70b7ceca5df5387258d861d4588082cea9500e731be001548c95afd8cd8c3af8"
    }
   }
  },
diff --git a/examples/tmaze_demo.ipynb b/examples/tmaze_demo.ipynb
index e710d33d..fddc373b 100644
--- a/examples/tmaze_demo.ipynb
+++ b/examples/tmaze_demo.ipynb
@@ -19,7 +19,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -27,8 +27,6 @@
     "import sys\n",
     "import pathlib\n",
     "import numpy as np\n",
-    "import seaborn as sns\n",
-    "import matplotlib.pyplot as plt\n",
     "import copy\n",
     "\n",
     "path = pathlib.Path(os.getcwd())\n",
@@ -36,40 +34,11 @@
     "sys.path.append(module_path)\n",
     "\n",
     "from pymdp.agent import Agent\n",
+    "from pymdp.utils import plot_beliefs, plot_likelihood\n",
     "from pymdp import utils\n",
     "from pymdp.envs import TMazeEnv"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Auxiliary Functions\n",
-    "\n",
-    "Define some utility functions that will be helpful for plotting."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def plot_beliefs(belief_dist, title=\"\"):\n",
-    "    plt.grid(zorder=0)\n",
-    "    plt.bar(range(belief_dist.shape[0]), belief_dist, color='r', zorder=3)\n",
-    "    plt.xticks(range(belief_dist.shape[0]))\n",
-    "    plt.title(title)\n",
-    "    plt.show()\n",
-    "    \n",
-    "def plot_likelihood(A, title=\"\"):\n",
-    "    ax = sns.heatmap(A, cmap=\"OrRd\", linewidth=2.5)\n",
-    "    plt.xticks(range(A.shape[1]))\n",
-    "    plt.yticks(range(A.shape[0]))\n",
-    "    plt.title(title)\n",
-    "    plt.show()"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -106,7 +75,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -122,7 +91,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -150,7 +119,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -159,31 +128,70 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAUwAAAD9CAYAAADXj047AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAAsTAAALEwEAmpwYAAAQHklEQVR4nO3de7CdVX3G8e9zDtIoUGiDbZFEpG20UrReGMChFTqFGphR7GgdcBzFOsZpG6dTbxN6QaQ3bKu2dnDKcUq9TcVLW5uOcaitglZBk6mXmlhqxNqEi1AEqiLS6K9/7Ddmc5Jz9jrJSc5K8v3MvDN7v3ud9a694Tz5rXe9+z2pKiRJk00t9QAk6WBhYEpSIwNTkhoZmJLUyMCUpEYGpiQ1MjC115JckuRf9+HnNyc5p7HtfyU5d2+PJS0GA7NTQ0B8O8k3k9yR5G1Jjl7qcbVK8pgkNYz/m8P7WTfepqp+uqquX4RjnZNk+772I01iYPbtmVV1NPAk4MnApUs1kCRH7OWPHje8h+cCv5vkvEUclnRAGZgHgaq6A7iOUXACkOTMJJ9Mcm+Sz+2c2ib5+ST/Ptbuw0k2jj3/eJJnD4/XJflykm8k2ZLkl8baXZLkE0nelORu4PIky5OsT/K/ST4N/MQC3sMmYPOs9/D9aXaShyd5e5J7knwxyWv2UDU+Kcnnk9yX5D1JliU5CvgQ8KixavZRreOSFsLAPAgkWQGcD2wdnp8IfBD4feCHgVcBf5vkkcBNwKokxyd5GPBERmFyTJKHA6cBHx+6/jLwc8CxwOuAdyU5YezQZwC3AD8K/AFwFfAAcALwK8PW+h7OBE7d+R724LXAY4AfB84DXrCHNs8DVgMnD+/rkqr61vDZ3FZVRw/bba3jkhbCwOzbB5J8A9gG3MkoVGAUJhuqakNVfa+qPgxsAi6oqm8DG4GnA08FPgd8AjgLOBP4UlXdDVBV76uq24Y+3gN8CTh97Pi3VdVfVNUO4EHgOcBlVfWtqvoC8PaG9/A/Sb4N3Ai8BfjAHO2eB/xhVd1TVduBN++hzZuH8X4d+EfGqlXpQDAw+/bsqjoGOAf4KeD4Yf9JwC8P0/F7k9wL/Cyjyg/ghuFnnj48vh44e9hu2Nl5khcm+exYH6eOHQNGQb3TI4EjZu37asN7OB44GnjlMKaHzdHuUbP63raHNneMPb5/6Fc6YAzMg0BV3QC8DfjTYdc24J1VddzYdlRVXTm8Pjswb2BWYCY5CXgrsBZYXlXHAV8AMn7oscd3ATuAlWP7Ht04/u9W1RsZTed/bY5mtwMrxp6vnKPdHg+xgLbSXjMwDx5/BpyX5GeAdwHPTPKMJNPD4sc5w7lOgE8Cj2M0vf50VW1mVJWeAXxsaHMUo6C5CyDJixlVmHtUVd8F/o7R4s8jkpwCvGiB7+FK4DVJlu3htfcClyb5oeEc7doF9Ps1YHmSYxc4HmlBDMyDRFXdBbyD0TnEbcCFwG8xCrxtwKsZ/nsOCyH/BmyuqgeHLm4EvlpVdw5ttgBvGPZ/DXgCo3Od81nLaBp8B6OK968X+DY+CNwDvHQPr10BbAe+Avwz8H7gOy2dVtV/AO8GbhlOL7hKrv0i3kBYPUryq8BFVXX2Uo9F2skKU11IckKSs5JMJXkco0Wiv1/qcUnjDEz14kjgauAbwEeAf2B0GZK0V5Jck+TOJF+Y4/UkeXOSrcMXIp4ysU+n5JIORUmeDnwTeEdV7bagmeQC4OXABYwWRP+8qs6Yr08rTEmHpKr6GPD1eZpcyChMq6puAo6b9U233ex2Q4Uka4A1AFdfffVT16xZsw9DlnQYyeQm87s8aZ7yvg5expBVg5mqmlnA4U7koV+Q2D7su32uH9gtMIcD7jyo83VJB8xCpryzsuqAaLpl1+XZ5384DmqXj5/nfeDupRtID5Yt3/XYz+L7D/0dWZza6gB/irfy0G+UrRj2zclzmJK6MbWAbRGsB144rJafCdxXVXNOx6GxwpSkA2ExK7gk72Z0T4Xjh3urvpbh5i9V9ZfABkYr5FsZ3czlxZP6NDAldWN6EfuqqosnvF7Ary+kTwNTUjd6PxNsYErqRu+LKgampG4YmJLUyCm5JDWywpSkRou5Sr4/GJiSumGFKUmNPIcpSY2sMCWpkYEpSY1c9JGkRlaYktTIRR9JamSFKUmNDExJauSUXJIauUouSY2ckktSIwNTkhp5DlOSGllhSlIjA1OSGk1N9T0pNzAldSMxMCWpiRWmJDWywpSkRrHClKQ2U9N9r5MbmJK64ZRckho5JZekRlaYktTIy4okqZEVpiQ1cpVckhr1vujTd5xLOqwkad4a+lqd5OYkW5Os28Prj07y0SSfSfL5JBdM6tPAlNSNTKV5m7efZBq4CjgfOAW4OMkps5r9DvDeqnoycBHwlknjMzAldWMRK8zTga1VdUtVPQhcC1w4q00BPzg8Pha4bVKnnsOU1I2FXFaUZA2wZmzXTFXNDI9PBLaNvbYdOGNWF5cD/5Tk5cBRwLmTjmlgSurGQlbJh3CcmdhwbhcDb6uqNyR5GvDOJKdW1ffm+gEDU1I3FvE6zFuBlWPPVwz7xr0EWA1QVTcmWQYcD9w5V6eew5TUjUy1bxNsBFYlOTnJkYwWddbPavPfwC8AJHk8sAy4a75OrTAldWOxKsyq2pFkLXAdMA1cU1Wbk1wBbKqq9cArgbcm+U1GC0CXVFXN16+BKakbi3nhelVtADbM2nfZ2OMtwFkL6dPAlNSNab8aKUltvPmGJDXq/bvkBqakblhhSlIjK0xJamSFKUmNpo6YXuohzMvAlNQPK0xJauM5TElqlCkvXJekJi76SFIrp+SS1GZq2lVySWrioo8ktTIwJalNGm6lvpQMTEndcEouSY3ioo8ktbHClKRGBqYkNfKbPpLU6lD4Lvnl8/+p3sPLsuVLPYJ++Fl8n78ji6P3KflucZ5kTZJNSTbNzMwsxZgkHaampqebt6WwW4VZVTPAzqT0n01JB0zvFWbbOcwH7t7Pw+jc2NTzys5PSu9v68annvffvnQD6cEjTtj12N+Rxemn898vF30kdePQqDAl6QDwjuuS1MjrMCWpUfwzu5LUxgpTkhq56CNJrawwJalN7xVm32v4kg4vU2nfJkiyOsnNSbYmWTdHm+cl2ZJkc5K/mdSnFaakbizWjDzJNHAVcB6wHdiYZH1VbRlrswq4FDirqu5J8iOT+rXClNSPxaswTwe2VtUtVfUgcC1w4aw2LwWuqqp7AKrqzonD24u3JEn7RbKQbded1YZtzVhXJwLbxp5vH/aNeyzw2CSfSHJTktWTxueUXFI/FjAnn3Vntb1xBLAKOAdYAXwsyROq6t65fsAKU1I/phawze9WYOXY8xXDvnHbgfVV9X9V9RXgPxkF6LzDk6QuZGqqeZtgI7AqyclJjgQuAtbPavMBRtUlSY5nNEW/Zb5OnZJL6sZirZJX1Y4ka4HrgGngmqranOQKYFNVrR9e+8UkW4DvAq+uqnlvbGpgSurHIl64XlUbgA2z9l029riAVwxbEwNTUj/6/qKPgSmpH96tSJIaZdrAlKQ2feelgSmpI07JJalN53lpYErqSOf3wzQwJXXDClOSGvV+x3UDU1I/DExJatT5nNzAlNSNzvPSwJTUkc4T08CU1I10fodeA1NSP1z0kaQ23q1IklpZYUpSIytMSWpkhSlJjaaml3oE8zIwJfXDClOSGnV+IaaBKakfVpiS1MhVcklqNOWUXJLaTLtKLkltnJJLUiMDU5IaeQ5TkhpZYUpSG/9qpCS1cpVckho5JZekRi76SFKjzivMvuNc0uElad8mdpXVSW5OsjXJunnaPSdJJTltUp9WmJL6sUiLPkmmgauA84DtwMYk66tqy6x2xwC/AXyqpV8rTEn9mEr7Nr/Tga1VdUtVPQhcC1y4h3a/B7weeKBpeAt5L5K0X2WqeUuyJsmmsW3NWE8nAtvGnm8f9u06VPIUYGVVfbB1eE7JJfVjAReuV9UMMLM3h0kyBbwRuGQhP2dgSurH4q2S3wqsHHu+Yti30zHAqcD1GR3zx4D1SZ5VVZvm6tTAlNSPxbsOcyOwKsnJjILyIuD5O1+sqvuA43c+T3I98Kr5whIMTEk9WaTArKodSdYC1wHTwDVVtTnJFcCmqlq/N/0amJL6sYh/NbKqNgAbZu27bI6257T0aWBK6kffX/QxMCV1pPOvRhqYkvphYEpSIwNTkhoZmJLUyMCUpEaHRGAuW76fh3HwWFe11EPoxyNOWOoR9MPfkcXReWDudpXo+B1AZmb26nvtkrSXsoDtwNutwpx1BxDLKUkHziHxZ3YfuHs/D6Nz49Ot+29funH0YGwafmXn06f97SGnZ/wdWZx+Ov9/ykUfSR0xMCWpjRWmJDUyMCWpUd95aWBK6sgi3g9zfzAwJfXDKbkkNTIwJalR33lpYErqiBWmJDVy0UeSGllhSlKjzgOz7/pXkjpihSmpH51XmAampH4YmJLUyFVySWpkhSlJjawwJamVFaYktXFKLkmNnJJLUiMDU5Ja9R2YfY9O0uElad8mdpXVSW5OsjXJuj28/ookW5J8Psm/JDlpUp8GpqR+LFJgJpkGrgLOB04BLk5yyqxmnwFOq6onAu8H/njS8AxMSR3JArZ5nQ5srapbqupB4FrgwvEGVfXRqrp/eHoTsGJSpwampH5MTTdvSdYk2TS2rRnr6URg29jz7cO+ubwE+NCk4bnoI6kj7ddhVtUMMLPPR0xeAJwGnD2prYEpqR+Ld1nRrcDKsecrhn0PPVxyLvDbwNlV9Z1JnRqYkrqRxfumz0ZgVZKTGQXlRcDzZx3rycDVwOqqurOlU89hSurI4iz6VNUOYC1wHfBF4L1VtTnJFUmeNTT7E+Bo4H1JPptk/aTRWWFK6sciftOnqjYAG2btu2zs8bkL7dPAlNQPvxopSY0MTElq5e3dJKmN98OUpEZOySWplRWmJLXJ9FKPYF4GpqR+eA5TkhoZmJLUykUfSWpjhSlJjbysSJJaWWFKUhun5JLUyim5JLWxwpSkVgamJLVxlVySGjkll6RWBqYktbHClKRWnsOUpDZWmJLUygpTkprEClOSWhmYktTGClOSWhmYktTGvxopSY2ckktSKwNTktpYYUpSKwNTktpYYUpSo85Xyfv+4qakw0wWsE3oKVmd5OYkW5Os28PrP5DkPcPrn0rymEl9GpiS+pG0b/N2k2ngKuB84BTg4iSnzGr2EuCeqvpJ4E3A6ycOr6rme33eFyVpzL6fgHzg7vbMWbZ8zuMleRpweVU9Y3h+KUBV/dFYm+uGNjcmOQK4A3hkzROKu1WYSdYk2TRs72JhNfIhuyV52VKPoZfNz8LPYo7PYg37atnytG6zsmrTrOOfCGwbe7592Mee2lTVDuA+YPl8w9stMKtqpqpOq6rTgMfvxVs+VO37/wyHDj+LXfwsdjmgn8V4Vg3bzP4+pucwJR2KbgVWjj1fMezbY5thSn4scPd8nRqYkg5FG4FVSU5OciRwEbB+Vpv1wIuGx88FPjLf+UuYfB3mfi9xDyJ+Frv4WeziZ7FLN59FVe1Isha4DpgGrqmqzUmuADZV1Xrgr4B3JtkKfJ1RqM5r0iq5JGnglFySGhmYktTIwJSkRgamJDUyMCWpkYEpSY0MTElq9P+7kcI4n3jwhwAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "plot_likelihood(A_gp[1][:,:,0],'Reward Right')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {
     "scrolled": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "plot_likelihood(A_gp[1][:,:,1],'Reward Left')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "plot_likelihood(A_gp[2][:,3,:],'Cue Mapping')"
    ]
@@ -199,7 +207,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -215,11 +223,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAUwAAAD9CAYAAADXj047AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAAsTAAALEwEAmpwYAAASmklEQVR4nO3df7RlZV3H8ffn3hGnhGAJWjEDgjGapJnKQl2mUEEOLBNTKzB/UOrUWmEtTQvThSO1Iit/trAci0woQV3mGmtcqCmiBjmT+WvGyInEmSF+NAiKioB8+2Pvm4fDvec8l7nM7Oa+X2vtNfvXefazz7nnO9/nefbeJ1WFJGm6mX1dAUn6/8KAKUmNDJiS1MiAKUmNDJiS1MiAKUmNDJj7WJIzk3xyX9cDIMk7kvxBP//kJFdN2PfIJLcmmd17Ndw7kmxNcuKE7R9M8oK9VyMNxX4dMJN8Jcm3+y/2dX1AOHBf12sxkhyQZH2SLyf5Zn9OFyQ56r48blV9oqoePlKPryQ5aWT7V6vqwKr67lIdcyQIz03Vn/Pc8pOX6liTVNWPVdVlfZ3WJ7lobPspVfU3e6MuGpb9OmD2fq6qDgR+AngM8Mp9VZEkK+7Fy94LPB14DnAw8GjgX4GfWcKqDcJIED6w/8wAHj2y7hNz+97L91LaI8shYAJQVdcBl9IFTgCSPCHJPye5Ocnn5pphSX4qyRdG9vtwks0jy59I8ox+/uwk/5nkG0m2Jfn5kf3OTPKpJG9MshtYn+TQJBuTfD3Jp4EfWajOfUZ3MnBaVW2uqjur6paqOr+q/qrf5/C+vJuSbE/y4pHXr0/y7iTv7Ou3NclxI9sfk+Qz/bZLgJUj205MsrOfvxA4EvhAn+n9TpKj+gxwxZ7Wo8UC7+WPJPlokt1J/ifJ3yY5ZOQ1X0ny8iSfT3JLkkuSrOy3HZbkH/rP/qb+M50Zed1JSdYCvwf8Un/en+u3X5bkRf38TJJXJ7kmyQ39OR7cb5t7j16Q5Kt9HV81Ur/jk2zp/xauT/KGxbwn2geqar+dgK8AJ/Xzq4EvAG/ul1cBu4FT6f7jOLlffhDwfcBtwGHA/YDrgV3AQf22bwOH9uX8AnB4X8YvAd8EfrjfdiZwJ/ASYEX/2ouBdwMPAB7Zl/vJBer/R8DHp5zj5cBb6YLdTwA3Aj/db1vfn8epwCxwHnBlv+0A4Brgpf05Phu4A/iDfvuJwM753st++SiggBV7Uo8p51bAMRPey2P6z+3+/ed2OfCmsTp/uv98Hgh8Cfj1ftt5wF/0534/4MlA5vm7WQ9cNFavy4AX9fO/CmwHHgocCLwPuHDsPXp7X99HA98BHtFvvwJ4Xj9/IPCEff2dcZo8LYcM8/1JvgHsAG4AXtOvfy6wqao2VdVdVfVhYAtwalV9G9gMPAV4HPA54FPAk4AnAF+uqt0AVfWeqrq2L+MS4MvA8SPHv7aq/qyq7gRuB54FnFNV36yqLwKT+sIOBf57oY1Jjujr9LtVdVtVfRb4S+D5I7t9sj/H7wIX0n1p6c/jfnQB5o6qem9/zou2h/VYjP97L6vq21W1vao+XFXfqaobgTcAJ4y95i3953MT8AG+18K4A/hh4CH9+X+iqu7NgxV+GXhDVV1dVbfSdfmcPtZl8Nq+vp+j+1uaO/c7gGOSHFZVt1bVlffi+NqLlkPAfEZVHUSXMf0oXdYI8BDgF/om2c1JbgZ+ku5LBPDx/jVP6ecvo/syntAvA5Dk+Uk+O1LGI0eOAV2gnvMguuxodN01E+q+e6Q+8zkcuKmqvjFW3qqR5etG5r8FrOy/zIcDu8aCxKS6TLIn9ViM0feNJD+Y5OIku5J8HbiIu7/38x13rm/0T+gyww8luTrJ2Yusy5zDufv7dg3dZ/yDDXV4IfAw4N+TbE7ytHtZB+0lyyFgAlBVHwfeAfxpv2oHXdPpkJHpAVX1R/328YD5ccYCZpKH0DW3zqJroh8CfBHI6KFH5m+ka1YeMbLuyAnV/ghwfJLVC2y/FnhgkoPGyts1ocw5/w2sSjJa10l1mZR97Uk9FmO8Dn/Yr3tUVf0AXash93jVfAVVfaOqfruqHko3qPayJPMNpE3LOq+l+893zpF0n/H1DXX4clWdATwYeB3w3iQPaKm/9o1lEzB7bwJOTvJoumzk55I8NclskpX9QMdccPpn4OF0zetPV9VWui/G4+n6yqDrhyy6QEiSX6HLMOfVN0ffRzdg8f1JjgUWvJ6vqj4CfBj4+ySPS7IiyUFJfj3Jr1bVjr6e5/X1/3G6rOWihcoccQXdF/s3k9wvyTO5e1fCuOvp+unmq+ee1GNPHATcCtySZBXwitYXJnlakmP6/zBuAb4L3DXPrtcDR80NCM3jXcBLkxyd7pK1PwQu6btgptXhuUkeVFV3ATf3q+ergwZiWQXMvp/rnXR9iDuA0+hGQW+kyzhfQf+eVNU3gc8AW6vq9r6IK4BrquqGfp9twOv79dcDj6Lr65zkLLom2XV0Ge9fT9n/2cAm4BK6L/YXgePosk+AM+gGF64F/h54TR9oJ+rP6Zl0gyk30Q1YvW/CS84DXt13Pbx8nu33qh576LXAY+nel39kcv3HraF7D2+l+/zeWlUfm2e/9/T/7k7ymXm2X0DXJ3s58F90g1svaazDWmBrkluBNwOn9/3nGqi5UUFJ0hTLKsOUpD1hwJS0X0p3C/ENSb64wPYkeUu6Gy0+n+Sx08o0YEraX72Drp94IafQ9WWvAdYBfz6tQAOmpP1SVV1ON6C5kNOAd1bnSuCQJJOue+YeFw4nWUcXbXnb2972uHXr1u1BlSUtI03XwE6yPmkehX4t/Bp9rOptqKoNizjcKu5+M8TOft2Cd9fdI2D2B5w7qEPokvaaxTR5x2LVXtF0a9r67PF/HNpPrB+9DO223fuuIhqWlYcuSTF7OdLs4u533a1myt1p9mFKGoyZRUxLYCPw/H60/AnALVW1YHMcGjNMSdobljKDS/IuuudBHJbu2a6voXtCF1X1F3R30J1K9xCWbwG/Mq1MA6akwVjKH4jqH2wyaXsBv7GYMg2YkgZj6KMlBkxJgzH0QRUDpqTBMGBKUiOb5JLUyAxTkhot5Sj5fcGAKWkwzDAlqZF9mJLUyAxTkhoZMCWpkYM+ktTIDFOSGjnoI0mNzDAlqZEBU5Ia2SSXpEaOkktSI5vkktTIgClJjezDlKRGZpiS1MiAKUmNZmaG3Sg3YEoajMSAKUlNzDAlqZEZpiQ1ihmmJLWZmR32OLkBU9Jg2CSXpEY2ySWpkRmmJDXysiJJamSGKUmNHCWXpEZDH/QZdjiXtKwkaZ4aylqb5Kok25OcPc/2I5N8LMm/Jfl8klOnlWnAlDQYmUnzNLGcZBY4HzgFOBY4I8mxY7u9Gnh3VT0GOB1467T6GTAlDcYSZpjHA9ur6uqquh24GDhtbJ8CfqCfPxi4dlqh9mFKGozFXFaUZB2wbmTVhqra0M+vAnaMbNsJPH6siPXAh5K8BHgAcNK0YxowJQ3GYkbJ++C4YeqOCzsDeEdVvT7JE4ELkzyyqu5a6AUGTEmDsYTXYe4CjhhZXt2vG/VCYC1AVV2RZCVwGHDDQoXahylpMDLTPk2xGViT5OgkB9AN6mwc2+erwM8AJHkEsBK4cVKhZpiSBmOpMsyqujPJWcClwCxwQVVtTXIusKWqNgK/Dbw9yUvpBoDOrKqaVK4BU9JgLOWF61W1Cdg0tu6ckfltwJMWU6YBU9JgzHprpCS18eEbktRo6PeSGzAlDYYZpiQ1MsOUpEZmmJLUaGbF7L6uwkQGTEnDYYYpSW3sw5SkRpnxwnVJauKgjyS1skkuSW1mZh0ll6QmDvpIUisDpiS1ScOj1PclA6akwbBJLkmN4qCPJLUxw5SkRgZMSWrknT6S1Mp7ySWpjU1ySWrkrZGS1MgMU5JaOegjSW3MMCWpkU9cl6RGXocpSY3iz+xKUhszTElq5KCPJLUyw5SkNkPPMIc9hi9peZlJ+zRFkrVJrkqyPcnZC+zzi0m2Jdma5O+mlWmGKWkwlqpFnmQWOB84GdgJbE6ysaq2jeyzBngl8KSq+lqSB08r1wxT0nAsXYZ5PLC9qq6uqtuBi4HTxvZ5MXB+VX0NoKpumFq9e3FKknSfSBYzZV2SLSPTupGiVgE7RpZ39utGPQx4WJJPJbkyydpp9bNJLmk4FtEmr6oNwIY9ONoKYA1wIrAauDzJo6rq5oVeYIYpaThmFjFNtgs4YmR5db9u1E5gY1XdUVX/BfwHXQCdWD1JGoTMzDRPU2wG1iQ5OskBwOnAxrF93k+XXZLkMLom+tWTCrVJLmkwlmqUvKruTHIWcCkwC1xQVVuTnAtsqaqN/bafTbIN+C7wiqraPalcA6ak4VjCC9erahOwaWzdOSPzBbysn5oYMCUNx7Bv9DFgShoOn1YkSY0ya8CUpDbDjpcGTEkDYpNcktoMPF4aMCUNyMCfh2nAlDQYZpiS1GjoT1w3YEoaDgOmJDUaeJvcgClpMAYeLw2YkgZk4BHTgClpMDLwJ/QaMCUNx/4w6LO+6r6uh/4/Wnnovq6B9jNDf1rRPRLg0V9i27BhT35fSJIWael+Zvc+cY8Mc+yX2EwtJe09A88w2/owb5v4MxdaTkaa4esH/setvWfJuu32hz5MSdorZmb3dQ0mMmBKGg4zTElqNPALMQ2YkobDDFOSGg18INGAKWk4ZmySS1KbWUfJJamNTXJJamTAlKRG9mFKUiMzTElq469GSlIrR8klqZFNcklq5KCPJDUaeIY57HAuaXlJ2qepRWVtkquSbE9y9oT9npWkkhw3rUwzTEnDsUSDPklmgfOBk4GdwOYkG6tq29h+BwG/BfxLS7lmmJKGY+l+BO14YHtVXV1VtwMXA6fNs9/vA68Dbmuq3mLORZLuU5lpnkZ/4baf1o2UtArYMbK8s1/3vUMljwWOqKp/bK2eTXJJw7GIC9fHfuF2UZLMAG8AzlzM6wyYkoZj6UbJdwFHjCyv7tfNOQh4JHBZumP+ELAxydOrastChRowJQ3H0l2HuRlYk+RoukB5OvCcuY1VdQtw2NxyksuAl08KlmDAlDQkSxQwq+rOJGcBlwKzwAVVtTXJucCWqtp4b8o1YEoajiX81ciq2gRsGlt3zgL7nthSpgFT0nAM+0YfA6akARn4rZEGTEnDYcCUpEYGTElqZMCUpEYGTElqZMCUpEYGTElqZcCUpDb+zK4kNbJJLkmtDJiS1MYMU5IaGTAlqdGw46UBU9KALOHzMO8LBkxJw2GTXJIaGTAlqdGw46UBU9KAmGFKUiMHfSSpkRmmJDUaeMAcdv4rSQNihilpOAaeYRowJQ2HAVOSGjlKLkmNzDAlqZEZpiS1MsOUpDY2ySWpkU1ySWpkwJSkVsMOmMOunaTlJWmfphaVtUmuSrI9ydnzbH9Zkm1JPp/kn5I8ZFqZBkxJw7FEATPJLHA+cApwLHBGkmPHdvs34Liq+nHgvcAfT6ueAVPSgGQR00THA9ur6uqquh24GDhtdIeq+lhVfatfvBJYPa1QA6ak4ZiZbZ6SrEuyZWRaN1LSKmDHyPLOft1CXgh8cFr1HPSRNCDt12FW1QZgwx4fMXkucBxwwrR9DZiShmPpLivaBRwxsry6X3f3wyUnAa8CTqiq70wr1IApaTCydHf6bAbWJDmaLlCeDjxn7FiPAd4GrK2qG1oKtQ9T0oAszaBPVd0JnAVcCnwJeHdVbU1ybpKn97v9CXAg8J4kn02ycVrtzDAlDccS3ulTVZuATWPrzhmZP2mxZRowJQ2Ht0ZKUiMDpiS18vFuktTG52FKUiOb5JLUygxTktpkdl/XYCIDpqThsA9TkhoZMCWplYM+ktTGDFOSGnlZkSS1MsOUpDY2ySWplU1ySWpjhilJrQyYktTGUXJJamSTXJJaGTAlqY0ZpiS1sg9TktqYYUpSKzNMSWoSM0xJamXAlKQ2ZpiS1MqAKUlt/NVISWpkk1ySWhkwJamNGaYktTJgSlIbM0xJajTwUfJh37gpaZnJIqYpJSVrk1yVZHuSs+fZfv8kl/Tb/yXJUdPKNGBKGo6kfZpYTGaB84FTgGOBM5IcO7bbC4GvVdUxwBuB102tXlVN2j5xoySN2PMOyNt2t8eclYcueLwkTwTWV9VT++VXAlTVeSP7XNrvc0WSFcB1wINqQlC8Rx9mknXAun7xoqp6XvMJaFlIsq6qNuzremhYluTvYkIQnO94fC9WAWwYOf4qYMfItp3A48eK+L99qurOJLcAhwL/s9Ax79Ekr6oNVXVcVR0HPKK18lpW1k3fRcvQXv27GI1V/XSf/yduH6ak/dEu4IiR5dX9unn36ZvkBwO7JxVqwJS0P9oMrElydJIDgNOBjWP7bARe0M8/G/jopP5LmH4dpv1Umo9/F5rPYP4u+j7Js4BLgVnggqramuRcYEtVbQT+CrgwyXbgJrqgOtG0UXJJUs8muSQ1MmBKUiMDpiQ1MmBKUiMDpiQ1MmBKUiMDpiQ1+l/ZPXI+kCzJVgAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "plot_likelihood(B_gp[1][:,:,0],'Reward Condition Transitions')"
    ]
@@ -244,38 +265,90 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "metadata": {
     "scrolled": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "plot_likelihood(B_gp[0][:,:,0],'Transition likelihood for \"Move to Center\"')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "plot_likelihood(B_gp[0][:,:,1],'Transition likelihood for \"Move to Right Arm\"')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "plot_likelihood(B_gp[0][:,:,2],'Transition likelihood for \"Move to Left Arm\"')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "plot_likelihood(B_gp[0][:,:,3],'Transition likelihood for \"Move to Cue Location\"')"
    ]
@@ -294,7 +367,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -336,7 +409,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -352,7 +425,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -368,22 +441,48 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "plot_beliefs(agent.D[0],\"Beliefs about initial location\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "metadata": {
     "scrolled": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "plot_beliefs(agent.D[1],\"Beliefs about reward condition\")"
    ]
@@ -397,7 +496,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -413,9 +512,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "plot_beliefs(agent.D[0],\"Beliefs about initial location\")"
    ]
@@ -433,7 +545,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -443,9 +555,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "plot_beliefs(agent.C[1],\"Prior beliefs about observations\")"
    ]
@@ -460,11 +585,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 23,
    "metadata": {
     "scrolled": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      " === Starting experiment === \n",
+      " Reward condition: Left, Observation: [CENTER, No reward, Cue Left]\n",
+      "[Step 0] Action: [Move to CUE LOCATION]\n",
+      "[Step 0] Observation: [CUE LOCATION,  No reward, Cue Left]\n",
+      "[Step 1] Action: [Move to LEFT ARM]\n",
+      "[Step 1] Observation: [LEFT ARM,  Reward!, Cue Left]\n",
+      "[Step 2] Action: [Move to LEFT ARM]\n",
+      "[Step 2] Observation: [LEFT ARM,  Reward!, Cue Right]\n",
+      "[Step 3] Action: [Move to LEFT ARM]\n",
+      "[Step 3] Observation: [LEFT ARM,  Reward!, Cue Right]\n",
+      "[Step 4] Action: [Move to LEFT ARM]\n",
+      "[Step 4] Observation: [LEFT ARM,  Reward!, Cue Right]\n"
+     ]
+    }
+   ],
    "source": [
     "T = 5 # number of timesteps\n",
     "\n",
@@ -510,20 +654,46 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 24,
    "metadata": {
     "scrolled": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "plot_likelihood(A_gp[2][:,:,0],'Cue Observations when condition is Reward on Right, for Different Locations')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 432x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "plot_likelihood(A_gp[2][:,:,1],'Cue Observations when condition is Reward on Left, for Different Locations')"
    ]
@@ -544,20 +714,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "plot_beliefs(qx[1],\"Final posterior beliefs about reward condition\")"
    ]
   }
  ],
  "metadata": {
-  "interpreter": {
-   "hash": "24ee14d9f6452059a99d44b6cbd71d1bb479b0539b0360a6a17428ecea9f0810"
-  },
   "kernelspec": {
-   "display_name": "Python 3.8.10 64-bit ('pymdp_env2': conda)",
+   "display_name": "Python 3.8.8 ('base')",
+   "language": "python",
    "name": "python3"
   },
   "language_info": {
@@ -570,7 +751,12 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.8.8"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "70b7ceca5df5387258d861d4588082cea9500e731be001548c95afd8cd8c3af8"
+   }
   }
  },
  "nbformat": 4,
diff --git a/examples/tmaze_learning_demo.ipynb b/examples/tmaze_learning_demo.ipynb
index 56523722..3692bb11 100644
--- a/examples/tmaze_learning_demo.ipynb
+++ b/examples/tmaze_learning_demo.ipynb
@@ -35,8 +35,6 @@
     "import sys\n",
     "import pathlib\n",
     "import numpy as np\n",
-    "import seaborn as sns\n",
-    "import matplotlib.pyplot as plt\n",
     "import copy\n",
     "\n",
     "path = pathlib.Path(os.getcwd())\n",
@@ -44,45 +42,16 @@
     "sys.path.append(module_path)\n",
     "\n",
     "from pymdp.agent import Agent\n",
+    "from pymdp.utils import plot_beliefs, plot_likelihood\n",
     "from pymdp import utils\n",
     "from pymdp.envs import TMazeEnvNullOutcome"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### Auxiliary Functions\n",
-    "\n",
-    "Define some utility functions that will be helpful for plotting."
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {},
    "outputs": [],
-   "source": [
-    "def plot_beliefs(belief_dist, title=\"\"):\n",
-    "    plt.grid(zorder=0)\n",
-    "    plt.bar(range(belief_dist.shape[0]), belief_dist, color='r', zorder=3)\n",
-    "    plt.xticks(range(belief_dist.shape[0]))\n",
-    "    plt.title(title)\n",
-    "    plt.show()\n",
-    "    \n",
-    "def plot_likelihood(A, title=\"\"):\n",
-    "    ax = sns.heatmap(A, cmap=\"OrRd\", linewidth=2.5)\n",
-    "    plt.xticks(range(A.shape[1]))\n",
-    "    plt.yticks(range(A.shape[0]))\n",
-    "    plt.title(title)\n",
-    "    plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [],
    "source": [
     "reward_probabilities = [0.85, 0.15] # the 'true' reward probabilities \n",
     "env = TMazeEnvNullOutcome(reward_probs = reward_probabilities)\n",
@@ -92,7 +61,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -105,14 +74,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "metadata": {
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -124,7 +93,7 @@
     },
     {
      "data": {
-      "image/png": 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IywF2sOGKozsBuDgi/o+kQ4FLJR0QEc+P9gIHXTPrKS08ZWwtMKvyfGaeV3UKMBcgIm6WNAXYDXhwtEZd0zWzntLCmu4yYLakfSS9EJgPLK5Z517gjXm7rwKmAA/Va9SZrpn1lL7+1mS6EfGspIXAtaT/2f2iiFgh6VxgeUQsBj4CfEnS6aRBtZMjIuq166BrZj2llVekRcQS0mlg1XlnVR6vBA4bS5sOumbWU/q6/Io0B10z6ym+94KZWUHdfu8FB10z6ynOdM3MCmrVvRfaxUHXzHqKywtmZgWpz5mumVkxrumamZXk8oKZWTl92/V3ugt1OeiaWU/xQJqZWUmu6ZqZleOzF8zMCnJ5wcysIJ8yZmZWkPp99oKZWTHOdM3MCnLQNTMrST57wcysGGe6ZmYFOehmZ9f/X4knlynTO92D7uFjsYm/I63R7WcvjLv4IekvWtkRM7NWUJ+anjphWyrO54y2QNKApOWSlg8ODm7DJszMxkZS01Mn1C0vSLpztEXAHqO9LiIGgeFo699MZlbMRL/3wh7Am4FHa+YL+Pcxbemph8e0ek+pqVtet+P2HepI5x294ektnsfapR3qSedpxhFbzvB3pCUm+kDad4CpEXF77QJJN7SlR2Zm20AT+X8DjohT6ixb0PrumJltm4leXjAzm1B8a0czs5ImeE3XzGxCcXnBzKwglxfMzAqa0GcvmJlNNN1+nm53/0kwMxsrjWFq1JQ0V9IqSaslnTnKOu+StFLSCkmXNWrTma6Z9ZYW1XQl9QMXAEcDQ8AySYsjYmVlndnAx4HDIuJRSS9u1K4zXTPrKVLzUwNzgNURsSYiNgKLgHk165wKXBARjwJExIONGnXQNbOeon41P1XuiJingUpTM4D7Ks+H8ryqlwMvl3STpFskzW3UP5cXzKy3jKG8UHNHxPHYDpgNHAnMBH4s6cCIeGy0FzjTNbPe0jeGqb61wKzK85l5XtUQsDginomIXwN3k4Jw3e6ZmfWMFt7EfBkwW9I+kl4IzAcW16zzTVKWi6TdSOWGNfUadXnBzHpLi85eiIhnJS0ErgX6gYsiYoWkc4HlEbE4L3uTpJXAc8AZEVH3xsgOumbWU1p5FXBELAGW1Mw7q/I4gL/OU1McdM2st/R39xVpDrpm1lN8wxszs5K6O+Y66JpZb+n2G9446JpZb+numOuga2Y9xjVdM7Ny5LMXzMzK6fJE10HXzHpMl0ddB10z6yldHnMddM2sx/iUMTOzcnyerplZSV1eX3DQNbOeoi6/S7iDrpn1Fme6ZmYFdXfMddA1s97iWzuamZXU391FXQddM+stPmXMzKygLj99wUHXzHqLa7pmZgW5vGBmVpDLC2ZmBfnsBTOzgvocdM3MyvFAmplZQc50zcwKcqZrZlZQf3+ne1CXg66Z9RZnumZm5fi/6zEzK8kXR5iZFeRM18ysINd0zcwK6vKzF7q7+GFmNlZS81PDpjRX0ipJqyWdWWe94yWFpIMbtelM18x6S4uuSJPUD1wAHA0MAcskLY6IlTXr7Qx8CLi1qe61pHdmZt2idZnuHGB1RKyJiI3AImDeCOv9A/AZ4Klmuuega2a9pU9NT5IGJC2vTAOVlmYA91WeD+V5m0h6PTArIr7bbPdcXjCz3jKG83QjYhAYHNdmpD7gfODksbzOQdfMekvrbmK+FphVeT4zzxu2M3AAcINSqeIlwGJJx0bE8tEaddA1s97Suls7LgNmS9qHFGznAwuGF0bEOmC34eeSbgA+Wi/ggmu6ZtZrWjSQFhHPAguBa4G7gCsjYoWkcyUdO97uOdM1s97SwivSImIJsKRm3lmjrHtkM2066JpZb/ENb8zMCvINb8zMCvINb8zMCnLQNTMryUHXzKyc7o65Drpm1mMmenlB0itJN3m4NSLWV+bPjYjvN72lKdPH1cFedPSGpzvdha6hGUd0ugvdw9+R1mjdFWltUbd3kv4K+BbwQeAXkqq3NftUnddtunPP4OC47iVhZjZOGsNUXqNM91TgoIhYL2lv4GpJe0fEP1GnxzV37olWdNTMrCndXV1oGHT7hksKEXGPpCNJgfdljHXXnnp4XB3sCTU/G2Pt0g51pPNqywnX7bh9h3rSeVuVmfwdaY0ur+k2Kn48IOm1w09yAP5T0p11Dmxnx8zMxqWF/0daOzTKdE8Enq3OyHfeOVHShW3rlZnZeE3key9ExFCdZTe1vjtmZtuoy8sLPk/XzHpLd8dcB10z6zHOdM3MSnLQNTMrx5mumVlBvom5mVlBznTNzEpy0DUzK8eZrplZQQ66ZmYFOeiamRXkoGtmVpCDrplZQQ66ZmYlOeiamZXjTNfMrCD1d7oHdTnomllvcaZrZlbQRP7veszMJh5numZm5XR5eaG783AzszHrG8NUn6S5klZJWi3pzBGW/7WklZLulPRDSS9rpndmZr2jr6/5qQ5J/cAFwFuA/YETJO1fs9ptwMER8RrgauCzDbs3rp0yM+taGsNU1xxgdUSsiYiNwCJgXnWFiLg+Ijbkp7cAMxs16qBrZr1FfU1PkgYkLa9MA5WWZgD3VZ4P5XmjOQX4XqPueSDNzHrLGAbSImIQGNz2Teo9wMHAEY3WddA1sx7TsrMX1gKzKs9n5nlbbk06Cvhb4IiIeLpRow66ZtZbWndxxDJgtqR9SMF2PrBgi01JrwMuBOZGxIPNNOqga2Y9RS0KuhHxrKSFwLVAP3BRRKyQdC6wPCIWA+cBU4GrlMoa90bEsfXaddA1s97SwsuAI2IJsKRm3lmVx0eNtU0HXTPrMd19RZqDrpn1li6/DNhB18x6i+8yZmZWkIOumVlBDrpmZiW5pmtmVo4H0szMSnJ5wcysHGe6ZmYF+b9gNzMryJmumVlJDrpmZuU40zUzK8lB18ysHGe6ZmYF+ewFM7OSnOmamZXj8oKZWUkOumZm5TjTNTMryPfTNTMryUHXzKwclxfMzEpy0DUzK8hB18ysGLm8YGZWkM9eMDMryZmumVk5znTNzEpypmtmVo4H0szMSnLQNTMrxzVdM7OCXF4wMyupu4Nud+fhZmZjpb7mp0ZNSXMlrZK0WtKZIyzfXtIVefmtkvZu2GZEjGu/xqDtGzCznrHtaeofHmo+5uyw+6jbk9QP3A0cDQwBy4ATImJlZZ2/BF4TEadJmg8cFxHvrrdJZ7pm1ltal+nOAVZHxJqI2AgsAubVrDMP+Gp+fDXwRjW4+UPba7qS3hcRg+3ezkQgacDHIvGx2MzHosWmTG86W5Y0AAxUZg1W3osZwH2VZUPAITVNbFonIp6VtA6YDvx+tG2WyHQHGq8yafhYbOZjsZmPRYdExGBEHFyZ2v7Hz+UFM7ORrQVmVZ7PzPNGXEfSdsCuwMP1GnXQNTMb2TJgtqR9JL0QmA8srllnMXBSfvxO4EfR4OyEEufpula1mY/FZj4Wm/lYdKFco10IXAv0AxdFxApJ5wLLI2Ix8BXgUkmrgUdIgbmuEqeMmZlZ5vKCmVlBDrpmZgW1Neg2uoRuspB0kaQHJf2i033pNEmzJF0vaaWkFZI+1Ok+dYqkKZJ+KumOfCzO6XSfrP3aVtNt5hK6yULS4cB64JKIOKDT/ekkSXsCe0bEzyXtDPwMePsk/VwI2Cki1kt6AXAj8KGIuKXDXbM2amem28wldJNCRPyYNLI56UXE/RHx8/z4CeAu0lU9k04k6/PTF+TJI9s9rp1Bd6RL6Cbll8tGlu/I9Drg1s72pHMk9Uu6HXgQuC4iJu2xmCw8kGYdIWkq8A3gwxHxeKf70ykR8VxEvJZ0tdMcSZO6/DQZtDPoNnMJnU1CuX75DeDrEfFvne5PN4iIx4Drgbmd7ou1VzuDbjOX0NkkkwePvgLcFRHnd7o/nSRpd0nT8uMdSIPOv+xsr6zd2hZ0I+JZYPgSuruAKyNiRbu2180kXQ7cDLxC0pCkUzrdpw46DPhz4A2Sbs/TMZ3uVIfsCVwv6U5SknJdRHynw32yNvNlwGZmBXkgzcysIAddM7OCHHTNzApy0DUzK8hB18ysIAddM7OCHHTNzAr6/4l9tBSoYOmUAAAAAElFTkSuQmCC",
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",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -142,12 +111,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -164,7 +133,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -173,7 +142,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -183,7 +152,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -196,7 +165,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -205,7 +174,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -215,7 +184,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -231,7 +200,7 @@
       "[Step 2] Action: [Move to RIGHT ARM]\n",
       "[Step 2] Observation: [RIGHT ARM,  Loss!, Null]\n",
       "[Step 3] Action: [Move to LEFT ARM]\n",
-      "[Step 3] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 3] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 4] Action: [Move to LEFT ARM]\n",
       "[Step 4] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 5] Action: [Move to LEFT ARM]\n",
@@ -247,17 +216,17 @@
       "[Step 10] Action: [Move to LEFT ARM]\n",
       "[Step 10] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 11] Action: [Move to LEFT ARM]\n",
-      "[Step 11] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 11] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 12] Action: [Move to LEFT ARM]\n",
-      "[Step 12] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 12] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 13] Action: [Move to LEFT ARM]\n",
-      "[Step 13] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 13] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 14] Action: [Move to LEFT ARM]\n",
       "[Step 14] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 15] Action: [Move to LEFT ARM]\n",
       "[Step 15] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 16] Action: [Move to LEFT ARM]\n",
-      "[Step 16] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 16] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 17] Action: [Move to LEFT ARM]\n",
       "[Step 17] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 18] Action: [Move to LEFT ARM]\n",
@@ -267,11 +236,11 @@
       "[Step 20] Action: [Move to LEFT ARM]\n",
       "[Step 20] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 21] Action: [Move to LEFT ARM]\n",
-      "[Step 21] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 21] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 22] Action: [Move to LEFT ARM]\n",
       "[Step 22] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 23] Action: [Move to LEFT ARM]\n",
-      "[Step 23] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 23] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 24] Action: [Move to LEFT ARM]\n",
       "[Step 24] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 25] Action: [Move to LEFT ARM]\n",
@@ -281,7 +250,7 @@
       "[Step 27] Action: [Move to LEFT ARM]\n",
       "[Step 27] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 28] Action: [Move to LEFT ARM]\n",
-      "[Step 28] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 28] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 29] Action: [Move to LEFT ARM]\n",
       "[Step 29] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 30] Action: [Move to LEFT ARM]\n",
@@ -303,19 +272,19 @@
       "[Step 38] Action: [Move to LEFT ARM]\n",
       "[Step 38] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 39] Action: [Move to LEFT ARM]\n",
-      "[Step 39] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 39] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 40] Action: [Move to LEFT ARM]\n",
-      "[Step 40] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 40] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 41] Action: [Move to LEFT ARM]\n",
       "[Step 41] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 42] Action: [Move to LEFT ARM]\n",
-      "[Step 42] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 42] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 43] Action: [Move to LEFT ARM]\n",
       "[Step 43] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 44] Action: [Move to LEFT ARM]\n",
       "[Step 44] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 45] Action: [Move to LEFT ARM]\n",
-      "[Step 45] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 45] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 46] Action: [Move to LEFT ARM]\n",
       "[Step 46] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 47] Action: [Move to LEFT ARM]\n",
@@ -329,11 +298,11 @@
       "[Step 51] Action: [Move to LEFT ARM]\n",
       "[Step 51] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 52] Action: [Move to LEFT ARM]\n",
-      "[Step 52] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 52] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 53] Action: [Move to LEFT ARM]\n",
       "[Step 53] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 54] Action: [Move to LEFT ARM]\n",
-      "[Step 54] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 54] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 55] Action: [Move to LEFT ARM]\n",
       "[Step 55] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 56] Action: [Move to LEFT ARM]\n",
@@ -357,21 +326,21 @@
       "[Step 65] Action: [Move to LEFT ARM]\n",
       "[Step 65] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 66] Action: [Move to LEFT ARM]\n",
-      "[Step 66] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 66] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 67] Action: [Move to LEFT ARM]\n",
-      "[Step 67] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 67] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 68] Action: [Move to LEFT ARM]\n",
-      "[Step 68] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 68] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 69] Action: [Move to LEFT ARM]\n",
-      "[Step 69] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 69] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 70] Action: [Move to LEFT ARM]\n",
       "[Step 70] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 71] Action: [Move to LEFT ARM]\n",
       "[Step 71] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 72] Action: [Move to LEFT ARM]\n",
-      "[Step 72] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 72] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 73] Action: [Move to LEFT ARM]\n",
-      "[Step 73] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 73] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 74] Action: [Move to LEFT ARM]\n",
       "[Step 74] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 75] Action: [Move to LEFT ARM]\n",
@@ -381,7 +350,7 @@
       "[Step 77] Action: [Move to LEFT ARM]\n",
       "[Step 77] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 78] Action: [Move to LEFT ARM]\n",
-      "[Step 78] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 78] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 79] Action: [Move to LEFT ARM]\n",
       "[Step 79] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 80] Action: [Move to LEFT ARM]\n",
@@ -391,13 +360,13 @@
       "[Step 82] Action: [Move to LEFT ARM]\n",
       "[Step 82] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 83] Action: [Move to LEFT ARM]\n",
-      "[Step 83] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 83] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 84] Action: [Move to LEFT ARM]\n",
       "[Step 84] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 85] Action: [Move to LEFT ARM]\n",
       "[Step 85] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 86] Action: [Move to LEFT ARM]\n",
-      "[Step 86] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 86] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 87] Action: [Move to LEFT ARM]\n",
       "[Step 87] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 88] Action: [Move to LEFT ARM]\n",
@@ -411,15 +380,15 @@
       "[Step 92] Action: [Move to LEFT ARM]\n",
       "[Step 92] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 93] Action: [Move to LEFT ARM]\n",
-      "[Step 93] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 93] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 94] Action: [Move to LEFT ARM]\n",
       "[Step 94] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 95] Action: [Move to LEFT ARM]\n",
       "[Step 95] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 96] Action: [Move to LEFT ARM]\n",
-      "[Step 96] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 96] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 97] Action: [Move to LEFT ARM]\n",
-      "[Step 97] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 97] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 98] Action: [Move to LEFT ARM]\n",
       "[Step 98] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 99] Action: [Move to LEFT ARM]\n",
@@ -429,7 +398,7 @@
       "[Step 101] Action: [Move to LEFT ARM]\n",
       "[Step 101] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 102] Action: [Move to LEFT ARM]\n",
-      "[Step 102] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 102] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 103] Action: [Move to LEFT ARM]\n",
       "[Step 103] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 104] Action: [Move to LEFT ARM]\n",
@@ -437,25 +406,25 @@
       "[Step 105] Action: [Move to LEFT ARM]\n",
       "[Step 105] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 106] Action: [Move to LEFT ARM]\n",
-      "[Step 106] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 106] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 107] Action: [Move to LEFT ARM]\n",
       "[Step 107] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 108] Action: [Move to LEFT ARM]\n",
-      "[Step 108] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 108] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 109] Action: [Move to LEFT ARM]\n",
       "[Step 109] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 110] Action: [Move to LEFT ARM]\n",
       "[Step 110] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 111] Action: [Move to LEFT ARM]\n",
-      "[Step 111] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 111] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 112] Action: [Move to LEFT ARM]\n",
       "[Step 112] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 113] Action: [Move to LEFT ARM]\n",
-      "[Step 113] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 113] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 114] Action: [Move to LEFT ARM]\n",
-      "[Step 114] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 114] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 115] Action: [Move to LEFT ARM]\n",
-      "[Step 115] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 115] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 116] Action: [Move to LEFT ARM]\n",
       "[Step 116] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 117] Action: [Move to LEFT ARM]\n",
@@ -463,7 +432,7 @@
       "[Step 118] Action: [Move to LEFT ARM]\n",
       "[Step 118] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 119] Action: [Move to LEFT ARM]\n",
-      "[Step 119] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 119] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 120] Action: [Move to LEFT ARM]\n",
       "[Step 120] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 121] Action: [Move to LEFT ARM]\n",
@@ -473,9 +442,9 @@
       "[Step 123] Action: [Move to LEFT ARM]\n",
       "[Step 123] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 124] Action: [Move to LEFT ARM]\n",
-      "[Step 124] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 124] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 125] Action: [Move to LEFT ARM]\n",
-      "[Step 125] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 125] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 126] Action: [Move to LEFT ARM]\n",
       "[Step 126] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 127] Action: [Move to LEFT ARM]\n",
@@ -485,7 +454,7 @@
       "[Step 129] Action: [Move to LEFT ARM]\n",
       "[Step 129] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 130] Action: [Move to LEFT ARM]\n",
-      "[Step 130] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 130] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 131] Action: [Move to LEFT ARM]\n",
       "[Step 131] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 132] Action: [Move to LEFT ARM]\n",
@@ -495,7 +464,7 @@
       "[Step 134] Action: [Move to LEFT ARM]\n",
       "[Step 134] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 135] Action: [Move to LEFT ARM]\n",
-      "[Step 135] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 135] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 136] Action: [Move to LEFT ARM]\n",
       "[Step 136] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 137] Action: [Move to LEFT ARM]\n",
@@ -509,13 +478,13 @@
       "[Step 141] Action: [Move to LEFT ARM]\n",
       "[Step 141] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 142] Action: [Move to LEFT ARM]\n",
-      "[Step 142] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 142] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 143] Action: [Move to LEFT ARM]\n",
-      "[Step 143] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 143] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 144] Action: [Move to LEFT ARM]\n",
       "[Step 144] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 145] Action: [Move to LEFT ARM]\n",
-      "[Step 145] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 145] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 146] Action: [Move to LEFT ARM]\n",
       "[Step 146] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 147] Action: [Move to LEFT ARM]\n",
@@ -523,7 +492,7 @@
       "[Step 148] Action: [Move to LEFT ARM]\n",
       "[Step 148] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 149] Action: [Move to LEFT ARM]\n",
-      "[Step 149] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 149] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 150] Action: [Move to LEFT ARM]\n",
       "[Step 150] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 151] Action: [Move to LEFT ARM]\n",
@@ -539,11 +508,11 @@
       "[Step 156] Action: [Move to LEFT ARM]\n",
       "[Step 156] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 157] Action: [Move to LEFT ARM]\n",
-      "[Step 157] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 157] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 158] Action: [Move to LEFT ARM]\n",
-      "[Step 158] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 158] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 159] Action: [Move to LEFT ARM]\n",
-      "[Step 159] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 159] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 160] Action: [Move to LEFT ARM]\n",
       "[Step 160] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 161] Action: [Move to LEFT ARM]\n",
@@ -555,9 +524,9 @@
       "[Step 164] Action: [Move to LEFT ARM]\n",
       "[Step 164] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 165] Action: [Move to LEFT ARM]\n",
-      "[Step 165] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 165] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 166] Action: [Move to LEFT ARM]\n",
-      "[Step 166] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 166] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 167] Action: [Move to LEFT ARM]\n",
       "[Step 167] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 168] Action: [Move to LEFT ARM]\n",
@@ -577,23 +546,23 @@
       "[Step 175] Action: [Move to LEFT ARM]\n",
       "[Step 175] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 176] Action: [Move to LEFT ARM]\n",
-      "[Step 176] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 176] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 177] Action: [Move to LEFT ARM]\n",
       "[Step 177] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 178] Action: [Move to LEFT ARM]\n",
       "[Step 178] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 179] Action: [Move to LEFT ARM]\n",
-      "[Step 179] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 179] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 180] Action: [Move to LEFT ARM]\n",
       "[Step 180] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 181] Action: [Move to LEFT ARM]\n",
-      "[Step 181] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 181] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 182] Action: [Move to LEFT ARM]\n",
-      "[Step 182] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 182] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 183] Action: [Move to LEFT ARM]\n",
       "[Step 183] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 184] Action: [Move to LEFT ARM]\n",
-      "[Step 184] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 184] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 185] Action: [Move to LEFT ARM]\n",
       "[Step 185] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 186] Action: [Move to LEFT ARM]\n",
@@ -603,7 +572,7 @@
       "[Step 188] Action: [Move to LEFT ARM]\n",
       "[Step 188] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 189] Action: [Move to LEFT ARM]\n",
-      "[Step 189] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 189] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 190] Action: [Move to LEFT ARM]\n",
       "[Step 190] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 191] Action: [Move to LEFT ARM]\n",
@@ -623,11 +592,11 @@
       "[Step 198] Action: [Move to LEFT ARM]\n",
       "[Step 198] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 199] Action: [Move to LEFT ARM]\n",
-      "[Step 199] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 199] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 200] Action: [Move to LEFT ARM]\n",
       "[Step 200] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 201] Action: [Move to LEFT ARM]\n",
-      "[Step 201] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 201] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 202] Action: [Move to LEFT ARM]\n",
       "[Step 202] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 203] Action: [Move to LEFT ARM]\n",
@@ -639,7 +608,7 @@
       "[Step 206] Action: [Move to LEFT ARM]\n",
       "[Step 206] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 207] Action: [Move to LEFT ARM]\n",
-      "[Step 207] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 207] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 208] Action: [Move to LEFT ARM]\n",
       "[Step 208] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 209] Action: [Move to LEFT ARM]\n",
@@ -653,9 +622,9 @@
       "[Step 213] Action: [Move to LEFT ARM]\n",
       "[Step 213] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 214] Action: [Move to LEFT ARM]\n",
-      "[Step 214] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 214] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 215] Action: [Move to LEFT ARM]\n",
-      "[Step 215] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 215] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 216] Action: [Move to LEFT ARM]\n",
       "[Step 216] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 217] Action: [Move to LEFT ARM]\n",
@@ -663,23 +632,23 @@
       "[Step 218] Action: [Move to LEFT ARM]\n",
       "[Step 218] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 219] Action: [Move to LEFT ARM]\n",
-      "[Step 219] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 219] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 220] Action: [Move to LEFT ARM]\n",
       "[Step 220] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 221] Action: [Move to LEFT ARM]\n",
-      "[Step 221] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 221] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 222] Action: [Move to LEFT ARM]\n",
       "[Step 222] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 223] Action: [Move to LEFT ARM]\n",
       "[Step 223] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 224] Action: [Move to LEFT ARM]\n",
-      "[Step 224] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 224] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 225] Action: [Move to LEFT ARM]\n",
       "[Step 225] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 226] Action: [Move to LEFT ARM]\n",
       "[Step 226] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 227] Action: [Move to LEFT ARM]\n",
-      "[Step 227] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 227] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 228] Action: [Move to LEFT ARM]\n",
       "[Step 228] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 229] Action: [Move to LEFT ARM]\n",
@@ -689,11 +658,11 @@
       "[Step 231] Action: [Move to LEFT ARM]\n",
       "[Step 231] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 232] Action: [Move to LEFT ARM]\n",
-      "[Step 232] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 232] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 233] Action: [Move to LEFT ARM]\n",
-      "[Step 233] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 233] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 234] Action: [Move to LEFT ARM]\n",
-      "[Step 234] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 234] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 235] Action: [Move to LEFT ARM]\n",
       "[Step 235] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 236] Action: [Move to LEFT ARM]\n",
@@ -713,15 +682,15 @@
       "[Step 243] Action: [Move to LEFT ARM]\n",
       "[Step 243] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 244] Action: [Move to LEFT ARM]\n",
-      "[Step 244] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 244] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 245] Action: [Move to LEFT ARM]\n",
       "[Step 245] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 246] Action: [Move to LEFT ARM]\n",
-      "[Step 246] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 246] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 247] Action: [Move to LEFT ARM]\n",
       "[Step 247] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 248] Action: [Move to LEFT ARM]\n",
-      "[Step 248] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 248] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 249] Action: [Move to LEFT ARM]\n",
       "[Step 249] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 250] Action: [Move to LEFT ARM]\n",
@@ -757,13 +726,13 @@
       "[Step 265] Action: [Move to LEFT ARM]\n",
       "[Step 265] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 266] Action: [Move to LEFT ARM]\n",
-      "[Step 266] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 266] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 267] Action: [Move to LEFT ARM]\n",
       "[Step 267] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 268] Action: [Move to LEFT ARM]\n",
       "[Step 268] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 269] Action: [Move to LEFT ARM]\n",
-      "[Step 269] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 269] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 270] Action: [Move to LEFT ARM]\n",
       "[Step 270] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 271] Action: [Move to LEFT ARM]\n",
@@ -779,7 +748,7 @@
       "[Step 276] Action: [Move to LEFT ARM]\n",
       "[Step 276] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 277] Action: [Move to LEFT ARM]\n",
-      "[Step 277] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 277] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 278] Action: [Move to LEFT ARM]\n",
       "[Step 278] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 279] Action: [Move to LEFT ARM]\n",
@@ -787,21 +756,21 @@
       "[Step 280] Action: [Move to LEFT ARM]\n",
       "[Step 280] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 281] Action: [Move to LEFT ARM]\n",
-      "[Step 281] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 281] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 282] Action: [Move to LEFT ARM]\n",
       "[Step 282] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 283] Action: [Move to LEFT ARM]\n",
-      "[Step 283] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 283] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 284] Action: [Move to LEFT ARM]\n",
-      "[Step 284] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 284] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 285] Action: [Move to LEFT ARM]\n",
-      "[Step 285] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 285] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 286] Action: [Move to LEFT ARM]\n",
-      "[Step 286] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 286] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 287] Action: [Move to LEFT ARM]\n",
-      "[Step 287] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 287] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 288] Action: [Move to LEFT ARM]\n",
-      "[Step 288] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 288] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 289] Action: [Move to LEFT ARM]\n",
       "[Step 289] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 290] Action: [Move to LEFT ARM]\n",
@@ -809,7 +778,7 @@
       "[Step 291] Action: [Move to LEFT ARM]\n",
       "[Step 291] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 292] Action: [Move to LEFT ARM]\n",
-      "[Step 292] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 292] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 293] Action: [Move to LEFT ARM]\n",
       "[Step 293] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 294] Action: [Move to LEFT ARM]\n",
@@ -821,11 +790,11 @@
       "[Step 297] Action: [Move to LEFT ARM]\n",
       "[Step 297] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 298] Action: [Move to LEFT ARM]\n",
-      "[Step 298] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 298] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 299] Action: [Move to LEFT ARM]\n",
       "[Step 299] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 300] Action: [Move to LEFT ARM]\n",
-      "[Step 300] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 300] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 301] Action: [Move to LEFT ARM]\n",
       "[Step 301] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 302] Action: [Move to LEFT ARM]\n",
@@ -835,9 +804,9 @@
       "[Step 304] Action: [Move to LEFT ARM]\n",
       "[Step 304] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 305] Action: [Move to LEFT ARM]\n",
-      "[Step 305] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 305] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 306] Action: [Move to LEFT ARM]\n",
-      "[Step 306] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 306] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 307] Action: [Move to LEFT ARM]\n",
       "[Step 307] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 308] Action: [Move to LEFT ARM]\n",
@@ -847,7 +816,7 @@
       "[Step 310] Action: [Move to LEFT ARM]\n",
       "[Step 310] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 311] Action: [Move to LEFT ARM]\n",
-      "[Step 311] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 311] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 312] Action: [Move to LEFT ARM]\n",
       "[Step 312] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 313] Action: [Move to LEFT ARM]\n",
@@ -855,21 +824,21 @@
       "[Step 314] Action: [Move to LEFT ARM]\n",
       "[Step 314] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 315] Action: [Move to LEFT ARM]\n",
-      "[Step 315] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 315] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 316] Action: [Move to LEFT ARM]\n",
-      "[Step 316] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 316] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 317] Action: [Move to LEFT ARM]\n",
       "[Step 317] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 318] Action: [Move to LEFT ARM]\n",
-      "[Step 318] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 318] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 319] Action: [Move to LEFT ARM]\n",
       "[Step 319] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 320] Action: [Move to LEFT ARM]\n",
       "[Step 320] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 321] Action: [Move to LEFT ARM]\n",
-      "[Step 321] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 321] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 322] Action: [Move to LEFT ARM]\n",
-      "[Step 322] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 322] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 323] Action: [Move to LEFT ARM]\n",
       "[Step 323] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 324] Action: [Move to LEFT ARM]\n",
@@ -883,7 +852,7 @@
       "[Step 328] Action: [Move to LEFT ARM]\n",
       "[Step 328] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 329] Action: [Move to LEFT ARM]\n",
-      "[Step 329] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 329] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 330] Action: [Move to LEFT ARM]\n",
       "[Step 330] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 331] Action: [Move to LEFT ARM]\n",
@@ -893,7 +862,7 @@
       "[Step 333] Action: [Move to LEFT ARM]\n",
       "[Step 333] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 334] Action: [Move to LEFT ARM]\n",
-      "[Step 334] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 334] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 335] Action: [Move to LEFT ARM]\n",
       "[Step 335] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 336] Action: [Move to LEFT ARM]\n",
@@ -903,19 +872,19 @@
       "[Step 338] Action: [Move to LEFT ARM]\n",
       "[Step 338] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 339] Action: [Move to LEFT ARM]\n",
-      "[Step 339] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 339] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 340] Action: [Move to LEFT ARM]\n",
-      "[Step 340] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 340] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 341] Action: [Move to LEFT ARM]\n",
       "[Step 341] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 342] Action: [Move to LEFT ARM]\n",
       "[Step 342] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 343] Action: [Move to LEFT ARM]\n",
-      "[Step 343] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 343] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 344] Action: [Move to LEFT ARM]\n",
       "[Step 344] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 345] Action: [Move to LEFT ARM]\n",
-      "[Step 345] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 345] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 346] Action: [Move to LEFT ARM]\n",
       "[Step 346] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 347] Action: [Move to LEFT ARM]\n",
@@ -935,7 +904,7 @@
       "[Step 354] Action: [Move to LEFT ARM]\n",
       "[Step 354] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 355] Action: [Move to LEFT ARM]\n",
-      "[Step 355] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 355] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 356] Action: [Move to LEFT ARM]\n",
       "[Step 356] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 357] Action: [Move to LEFT ARM]\n",
@@ -953,7 +922,7 @@
       "[Step 363] Action: [Move to LEFT ARM]\n",
       "[Step 363] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 364] Action: [Move to LEFT ARM]\n",
-      "[Step 364] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 364] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 365] Action: [Move to LEFT ARM]\n",
       "[Step 365] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 366] Action: [Move to LEFT ARM]\n",
@@ -963,17 +932,17 @@
       "[Step 368] Action: [Move to LEFT ARM]\n",
       "[Step 368] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 369] Action: [Move to LEFT ARM]\n",
-      "[Step 369] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 369] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 370] Action: [Move to LEFT ARM]\n",
       "[Step 370] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 371] Action: [Move to LEFT ARM]\n",
-      "[Step 371] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 371] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 372] Action: [Move to LEFT ARM]\n",
       "[Step 372] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 373] Action: [Move to LEFT ARM]\n",
       "[Step 373] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 374] Action: [Move to LEFT ARM]\n",
-      "[Step 374] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 374] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 375] Action: [Move to LEFT ARM]\n",
       "[Step 375] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 376] Action: [Move to LEFT ARM]\n",
@@ -981,15 +950,15 @@
       "[Step 377] Action: [Move to LEFT ARM]\n",
       "[Step 377] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 378] Action: [Move to LEFT ARM]\n",
-      "[Step 378] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 378] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 379] Action: [Move to LEFT ARM]\n",
-      "[Step 379] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 379] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 380] Action: [Move to LEFT ARM]\n",
       "[Step 380] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 381] Action: [Move to LEFT ARM]\n",
-      "[Step 381] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 381] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 382] Action: [Move to LEFT ARM]\n",
-      "[Step 382] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 382] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 383] Action: [Move to LEFT ARM]\n",
       "[Step 383] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 384] Action: [Move to LEFT ARM]\n",
@@ -1001,13 +970,13 @@
       "[Step 387] Action: [Move to LEFT ARM]\n",
       "[Step 387] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 388] Action: [Move to LEFT ARM]\n",
-      "[Step 388] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 388] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 389] Action: [Move to LEFT ARM]\n",
       "[Step 389] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 390] Action: [Move to LEFT ARM]\n",
       "[Step 390] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 391] Action: [Move to LEFT ARM]\n",
-      "[Step 391] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 391] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 392] Action: [Move to LEFT ARM]\n",
       "[Step 392] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 393] Action: [Move to LEFT ARM]\n",
@@ -1015,17 +984,17 @@
       "[Step 394] Action: [Move to LEFT ARM]\n",
       "[Step 394] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 395] Action: [Move to LEFT ARM]\n",
-      "[Step 395] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 395] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 396] Action: [Move to LEFT ARM]\n",
-      "[Step 396] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 396] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 397] Action: [Move to LEFT ARM]\n",
       "[Step 397] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 398] Action: [Move to LEFT ARM]\n",
       "[Step 398] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 399] Action: [Move to LEFT ARM]\n",
-      "[Step 399] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 399] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 400] Action: [Move to LEFT ARM]\n",
-      "[Step 400] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 400] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 401] Action: [Move to LEFT ARM]\n",
       "[Step 401] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 402] Action: [Move to LEFT ARM]\n",
@@ -1033,19 +1002,19 @@
       "[Step 403] Action: [Move to LEFT ARM]\n",
       "[Step 403] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 404] Action: [Move to LEFT ARM]\n",
-      "[Step 404] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 404] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 405] Action: [Move to LEFT ARM]\n",
       "[Step 405] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 406] Action: [Move to LEFT ARM]\n",
       "[Step 406] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 407] Action: [Move to LEFT ARM]\n",
-      "[Step 407] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 407] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 408] Action: [Move to LEFT ARM]\n",
       "[Step 408] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 409] Action: [Move to LEFT ARM]\n",
-      "[Step 409] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 409] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 410] Action: [Move to LEFT ARM]\n",
-      "[Step 410] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 410] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 411] Action: [Move to LEFT ARM]\n",
       "[Step 411] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 412] Action: [Move to LEFT ARM]\n",
@@ -1059,13 +1028,13 @@
       "[Step 416] Action: [Move to LEFT ARM]\n",
       "[Step 416] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 417] Action: [Move to LEFT ARM]\n",
-      "[Step 417] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 417] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 418] Action: [Move to LEFT ARM]\n",
-      "[Step 418] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 418] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 419] Action: [Move to LEFT ARM]\n",
-      "[Step 419] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 419] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 420] Action: [Move to LEFT ARM]\n",
-      "[Step 420] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 420] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 421] Action: [Move to LEFT ARM]\n",
       "[Step 421] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 422] Action: [Move to LEFT ARM]\n",
@@ -1081,23 +1050,23 @@
       "[Step 427] Action: [Move to LEFT ARM]\n",
       "[Step 427] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 428] Action: [Move to LEFT ARM]\n",
-      "[Step 428] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 428] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 429] Action: [Move to LEFT ARM]\n",
-      "[Step 429] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 429] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 430] Action: [Move to LEFT ARM]\n",
       "[Step 430] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 431] Action: [Move to LEFT ARM]\n",
-      "[Step 431] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 431] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 432] Action: [Move to LEFT ARM]\n",
       "[Step 432] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 433] Action: [Move to LEFT ARM]\n",
-      "[Step 433] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 433] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 434] Action: [Move to LEFT ARM]\n",
       "[Step 434] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 435] Action: [Move to LEFT ARM]\n",
       "[Step 435] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 436] Action: [Move to LEFT ARM]\n",
-      "[Step 436] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 436] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 437] Action: [Move to LEFT ARM]\n",
       "[Step 437] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 438] Action: [Move to LEFT ARM]\n",
@@ -1105,13 +1074,13 @@
       "[Step 439] Action: [Move to LEFT ARM]\n",
       "[Step 439] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 440] Action: [Move to LEFT ARM]\n",
-      "[Step 440] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 440] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 441] Action: [Move to LEFT ARM]\n",
       "[Step 441] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 442] Action: [Move to LEFT ARM]\n",
       "[Step 442] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 443] Action: [Move to LEFT ARM]\n",
-      "[Step 443] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 443] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 444] Action: [Move to LEFT ARM]\n",
       "[Step 444] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 445] Action: [Move to LEFT ARM]\n",
@@ -1121,7 +1090,7 @@
       "[Step 447] Action: [Move to LEFT ARM]\n",
       "[Step 447] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 448] Action: [Move to LEFT ARM]\n",
-      "[Step 448] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 448] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 449] Action: [Move to LEFT ARM]\n",
       "[Step 449] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 450] Action: [Move to LEFT ARM]\n",
@@ -1129,15 +1098,15 @@
       "[Step 451] Action: [Move to LEFT ARM]\n",
       "[Step 451] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 452] Action: [Move to LEFT ARM]\n",
-      "[Step 452] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 452] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 453] Action: [Move to LEFT ARM]\n",
       "[Step 453] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 454] Action: [Move to LEFT ARM]\n",
       "[Step 454] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 455] Action: [Move to LEFT ARM]\n",
-      "[Step 455] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 455] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 456] Action: [Move to LEFT ARM]\n",
-      "[Step 456] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 456] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 457] Action: [Move to LEFT ARM]\n",
       "[Step 457] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 458] Action: [Move to LEFT ARM]\n",
@@ -1149,9 +1118,9 @@
       "[Step 461] Action: [Move to LEFT ARM]\n",
       "[Step 461] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 462] Action: [Move to LEFT ARM]\n",
-      "[Step 462] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 462] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 463] Action: [Move to LEFT ARM]\n",
-      "[Step 463] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 463] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 464] Action: [Move to LEFT ARM]\n",
       "[Step 464] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 465] Action: [Move to LEFT ARM]\n",
@@ -1167,7 +1136,7 @@
       "[Step 470] Action: [Move to LEFT ARM]\n",
       "[Step 470] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 471] Action: [Move to LEFT ARM]\n",
-      "[Step 471] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 471] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 472] Action: [Move to LEFT ARM]\n",
       "[Step 472] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 473] Action: [Move to LEFT ARM]\n",
@@ -1181,15 +1150,15 @@
       "[Step 477] Action: [Move to LEFT ARM]\n",
       "[Step 477] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 478] Action: [Move to LEFT ARM]\n",
-      "[Step 478] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 478] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 479] Action: [Move to LEFT ARM]\n",
       "[Step 479] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 480] Action: [Move to LEFT ARM]\n",
       "[Step 480] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 481] Action: [Move to LEFT ARM]\n",
-      "[Step 481] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 481] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 482] Action: [Move to LEFT ARM]\n",
-      "[Step 482] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 482] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 483] Action: [Move to LEFT ARM]\n",
       "[Step 483] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 484] Action: [Move to LEFT ARM]\n",
@@ -1207,7 +1176,7 @@
       "[Step 490] Action: [Move to LEFT ARM]\n",
       "[Step 490] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 491] Action: [Move to LEFT ARM]\n",
-      "[Step 491] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 491] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 492] Action: [Move to LEFT ARM]\n",
       "[Step 492] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 493] Action: [Move to LEFT ARM]\n",
@@ -1229,25 +1198,25 @@
       "[Step 501] Action: [Move to LEFT ARM]\n",
       "[Step 501] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 502] Action: [Move to LEFT ARM]\n",
-      "[Step 502] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 502] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 503] Action: [Move to LEFT ARM]\n",
-      "[Step 503] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 503] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 504] Action: [Move to LEFT ARM]\n",
       "[Step 504] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 505] Action: [Move to LEFT ARM]\n",
-      "[Step 505] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 505] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 506] Action: [Move to LEFT ARM]\n",
       "[Step 506] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 507] Action: [Move to LEFT ARM]\n",
-      "[Step 507] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 507] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 508] Action: [Move to LEFT ARM]\n",
       "[Step 508] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 509] Action: [Move to LEFT ARM]\n",
-      "[Step 509] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 509] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 510] Action: [Move to LEFT ARM]\n",
       "[Step 510] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 511] Action: [Move to LEFT ARM]\n",
-      "[Step 511] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 511] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 512] Action: [Move to LEFT ARM]\n",
       "[Step 512] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 513] Action: [Move to LEFT ARM]\n",
@@ -1255,23 +1224,23 @@
       "[Step 514] Action: [Move to LEFT ARM]\n",
       "[Step 514] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 515] Action: [Move to LEFT ARM]\n",
-      "[Step 515] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 515] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 516] Action: [Move to LEFT ARM]\n",
       "[Step 516] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 517] Action: [Move to LEFT ARM]\n",
       "[Step 517] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 518] Action: [Move to LEFT ARM]\n",
-      "[Step 518] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 518] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 519] Action: [Move to LEFT ARM]\n",
       "[Step 519] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 520] Action: [Move to LEFT ARM]\n",
       "[Step 520] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 521] Action: [Move to LEFT ARM]\n",
-      "[Step 521] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 521] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 522] Action: [Move to LEFT ARM]\n",
-      "[Step 522] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 522] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 523] Action: [Move to LEFT ARM]\n",
-      "[Step 523] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 523] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 524] Action: [Move to LEFT ARM]\n",
       "[Step 524] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 525] Action: [Move to LEFT ARM]\n",
@@ -1297,7 +1266,7 @@
       "[Step 535] Action: [Move to LEFT ARM]\n",
       "[Step 535] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 536] Action: [Move to LEFT ARM]\n",
-      "[Step 536] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 536] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 537] Action: [Move to LEFT ARM]\n",
       "[Step 537] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 538] Action: [Move to LEFT ARM]\n",
@@ -1309,7 +1278,7 @@
       "[Step 541] Action: [Move to LEFT ARM]\n",
       "[Step 541] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 542] Action: [Move to LEFT ARM]\n",
-      "[Step 542] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 542] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 543] Action: [Move to LEFT ARM]\n",
       "[Step 543] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 544] Action: [Move to LEFT ARM]\n",
@@ -1319,7 +1288,7 @@
       "[Step 546] Action: [Move to LEFT ARM]\n",
       "[Step 546] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 547] Action: [Move to LEFT ARM]\n",
-      "[Step 547] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 547] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 548] Action: [Move to LEFT ARM]\n",
       "[Step 548] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 549] Action: [Move to LEFT ARM]\n",
@@ -1327,29 +1296,29 @@
       "[Step 550] Action: [Move to LEFT ARM]\n",
       "[Step 550] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 551] Action: [Move to LEFT ARM]\n",
-      "[Step 551] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 551] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 552] Action: [Move to LEFT ARM]\n",
       "[Step 552] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 553] Action: [Move to LEFT ARM]\n",
-      "[Step 553] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 553] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 554] Action: [Move to LEFT ARM]\n",
-      "[Step 554] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 554] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 555] Action: [Move to LEFT ARM]\n",
       "[Step 555] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 556] Action: [Move to LEFT ARM]\n",
       "[Step 556] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 557] Action: [Move to LEFT ARM]\n",
-      "[Step 557] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 557] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 558] Action: [Move to LEFT ARM]\n",
       "[Step 558] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 559] Action: [Move to LEFT ARM]\n",
       "[Step 559] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 560] Action: [Move to LEFT ARM]\n",
-      "[Step 560] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 560] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 561] Action: [Move to LEFT ARM]\n",
       "[Step 561] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 562] Action: [Move to LEFT ARM]\n",
-      "[Step 562] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 562] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 563] Action: [Move to LEFT ARM]\n",
       "[Step 563] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 564] Action: [Move to LEFT ARM]\n",
@@ -1365,7 +1334,7 @@
       "[Step 569] Action: [Move to LEFT ARM]\n",
       "[Step 569] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 570] Action: [Move to LEFT ARM]\n",
-      "[Step 570] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 570] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 571] Action: [Move to LEFT ARM]\n",
       "[Step 571] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 572] Action: [Move to LEFT ARM]\n",
@@ -1373,7 +1342,7 @@
       "[Step 573] Action: [Move to LEFT ARM]\n",
       "[Step 573] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 574] Action: [Move to LEFT ARM]\n",
-      "[Step 574] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 574] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 575] Action: [Move to LEFT ARM]\n",
       "[Step 575] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 576] Action: [Move to LEFT ARM]\n",
@@ -1389,7 +1358,7 @@
       "[Step 581] Action: [Move to LEFT ARM]\n",
       "[Step 581] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 582] Action: [Move to LEFT ARM]\n",
-      "[Step 582] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 582] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 583] Action: [Move to LEFT ARM]\n",
       "[Step 583] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 584] Action: [Move to LEFT ARM]\n",
@@ -1405,15 +1374,15 @@
       "[Step 589] Action: [Move to LEFT ARM]\n",
       "[Step 589] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 590] Action: [Move to LEFT ARM]\n",
-      "[Step 590] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 590] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 591] Action: [Move to LEFT ARM]\n",
       "[Step 591] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 592] Action: [Move to LEFT ARM]\n",
       "[Step 592] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 593] Action: [Move to LEFT ARM]\n",
-      "[Step 593] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 593] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 594] Action: [Move to LEFT ARM]\n",
-      "[Step 594] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 594] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 595] Action: [Move to LEFT ARM]\n",
       "[Step 595] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 596] Action: [Move to LEFT ARM]\n",
@@ -1431,7 +1400,7 @@
       "[Step 602] Action: [Move to LEFT ARM]\n",
       "[Step 602] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 603] Action: [Move to LEFT ARM]\n",
-      "[Step 603] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 603] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 604] Action: [Move to LEFT ARM]\n",
       "[Step 604] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 605] Action: [Move to LEFT ARM]\n",
@@ -1439,11 +1408,11 @@
       "[Step 606] Action: [Move to LEFT ARM]\n",
       "[Step 606] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 607] Action: [Move to LEFT ARM]\n",
-      "[Step 607] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 607] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 608] Action: [Move to LEFT ARM]\n",
       "[Step 608] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 609] Action: [Move to LEFT ARM]\n",
-      "[Step 609] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 609] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 610] Action: [Move to LEFT ARM]\n",
       "[Step 610] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 611] Action: [Move to LEFT ARM]\n",
@@ -1455,23 +1424,23 @@
       "[Step 614] Action: [Move to LEFT ARM]\n",
       "[Step 614] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 615] Action: [Move to LEFT ARM]\n",
-      "[Step 615] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 615] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 616] Action: [Move to LEFT ARM]\n",
-      "[Step 616] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 616] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 617] Action: [Move to LEFT ARM]\n",
       "[Step 617] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 618] Action: [Move to LEFT ARM]\n",
-      "[Step 618] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 618] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 619] Action: [Move to LEFT ARM]\n",
       "[Step 619] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 620] Action: [Move to LEFT ARM]\n",
       "[Step 620] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 621] Action: [Move to LEFT ARM]\n",
-      "[Step 621] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 621] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 622] Action: [Move to LEFT ARM]\n",
-      "[Step 622] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 622] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 623] Action: [Move to LEFT ARM]\n",
-      "[Step 623] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 623] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 624] Action: [Move to LEFT ARM]\n",
       "[Step 624] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 625] Action: [Move to LEFT ARM]\n",
@@ -1499,7 +1468,7 @@
       "[Step 636] Action: [Move to LEFT ARM]\n",
       "[Step 636] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 637] Action: [Move to LEFT ARM]\n",
-      "[Step 637] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 637] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 638] Action: [Move to LEFT ARM]\n",
       "[Step 638] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 639] Action: [Move to LEFT ARM]\n",
@@ -1511,7 +1480,7 @@
       "[Step 642] Action: [Move to LEFT ARM]\n",
       "[Step 642] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 643] Action: [Move to LEFT ARM]\n",
-      "[Step 643] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 643] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 644] Action: [Move to LEFT ARM]\n",
       "[Step 644] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 645] Action: [Move to LEFT ARM]\n",
@@ -1523,7 +1492,7 @@
       "[Step 648] Action: [Move to LEFT ARM]\n",
       "[Step 648] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 649] Action: [Move to LEFT ARM]\n",
-      "[Step 649] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 649] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 650] Action: [Move to LEFT ARM]\n",
       "[Step 650] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 651] Action: [Move to LEFT ARM]\n",
@@ -1531,7 +1500,7 @@
       "[Step 652] Action: [Move to LEFT ARM]\n",
       "[Step 652] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 653] Action: [Move to LEFT ARM]\n",
-      "[Step 653] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 653] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 654] Action: [Move to LEFT ARM]\n",
       "[Step 654] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 655] Action: [Move to LEFT ARM]\n",
@@ -1553,13 +1522,13 @@
       "[Step 663] Action: [Move to LEFT ARM]\n",
       "[Step 663] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 664] Action: [Move to LEFT ARM]\n",
-      "[Step 664] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 664] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 665] Action: [Move to LEFT ARM]\n",
       "[Step 665] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 666] Action: [Move to LEFT ARM]\n",
       "[Step 666] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 667] Action: [Move to LEFT ARM]\n",
-      "[Step 667] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 667] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 668] Action: [Move to LEFT ARM]\n",
       "[Step 668] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 669] Action: [Move to LEFT ARM]\n",
@@ -1579,7 +1548,7 @@
       "[Step 676] Action: [Move to LEFT ARM]\n",
       "[Step 676] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 677] Action: [Move to LEFT ARM]\n",
-      "[Step 677] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 677] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 678] Action: [Move to LEFT ARM]\n",
       "[Step 678] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 679] Action: [Move to LEFT ARM]\n",
@@ -1587,11 +1556,11 @@
       "[Step 680] Action: [Move to LEFT ARM]\n",
       "[Step 680] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 681] Action: [Move to LEFT ARM]\n",
-      "[Step 681] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 681] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 682] Action: [Move to LEFT ARM]\n",
       "[Step 682] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 683] Action: [Move to LEFT ARM]\n",
-      "[Step 683] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 683] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 684] Action: [Move to LEFT ARM]\n",
       "[Step 684] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 685] Action: [Move to LEFT ARM]\n",
@@ -1607,7 +1576,7 @@
       "[Step 690] Action: [Move to LEFT ARM]\n",
       "[Step 690] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 691] Action: [Move to LEFT ARM]\n",
-      "[Step 691] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 691] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 692] Action: [Move to LEFT ARM]\n",
       "[Step 692] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 693] Action: [Move to LEFT ARM]\n",
@@ -1617,17 +1586,17 @@
       "[Step 695] Action: [Move to LEFT ARM]\n",
       "[Step 695] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 696] Action: [Move to LEFT ARM]\n",
-      "[Step 696] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 696] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 697] Action: [Move to LEFT ARM]\n",
       "[Step 697] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 698] Action: [Move to LEFT ARM]\n",
       "[Step 698] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 699] Action: [Move to LEFT ARM]\n",
-      "[Step 699] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 699] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 700] Action: [Move to LEFT ARM]\n",
       "[Step 700] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 701] Action: [Move to LEFT ARM]\n",
-      "[Step 701] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 701] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 702] Action: [Move to LEFT ARM]\n",
       "[Step 702] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 703] Action: [Move to LEFT ARM]\n",
@@ -1639,11 +1608,11 @@
       "[Step 706] Action: [Move to LEFT ARM]\n",
       "[Step 706] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 707] Action: [Move to LEFT ARM]\n",
-      "[Step 707] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 707] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 708] Action: [Move to LEFT ARM]\n",
       "[Step 708] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 709] Action: [Move to LEFT ARM]\n",
-      "[Step 709] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 709] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 710] Action: [Move to LEFT ARM]\n",
       "[Step 710] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 711] Action: [Move to LEFT ARM]\n",
@@ -1659,13 +1628,13 @@
       "[Step 716] Action: [Move to LEFT ARM]\n",
       "[Step 716] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 717] Action: [Move to LEFT ARM]\n",
-      "[Step 717] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 717] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 718] Action: [Move to LEFT ARM]\n",
       "[Step 718] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 719] Action: [Move to LEFT ARM]\n",
       "[Step 719] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 720] Action: [Move to LEFT ARM]\n",
-      "[Step 720] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 720] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 721] Action: [Move to LEFT ARM]\n",
       "[Step 721] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 722] Action: [Move to LEFT ARM]\n",
@@ -1673,31 +1642,31 @@
       "[Step 723] Action: [Move to LEFT ARM]\n",
       "[Step 723] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 724] Action: [Move to LEFT ARM]\n",
-      "[Step 724] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 724] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 725] Action: [Move to LEFT ARM]\n",
-      "[Step 725] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 725] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 726] Action: [Move to LEFT ARM]\n",
       "[Step 726] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 727] Action: [Move to LEFT ARM]\n",
       "[Step 727] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 728] Action: [Move to LEFT ARM]\n",
-      "[Step 728] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 728] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 729] Action: [Move to LEFT ARM]\n",
       "[Step 729] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 730] Action: [Move to LEFT ARM]\n",
-      "[Step 730] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 730] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 731] Action: [Move to LEFT ARM]\n",
       "[Step 731] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 732] Action: [Move to LEFT ARM]\n",
       "[Step 732] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 733] Action: [Move to LEFT ARM]\n",
-      "[Step 733] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 733] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 734] Action: [Move to LEFT ARM]\n",
       "[Step 734] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 735] Action: [Move to LEFT ARM]\n",
       "[Step 735] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 736] Action: [Move to LEFT ARM]\n",
-      "[Step 736] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 736] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 737] Action: [Move to LEFT ARM]\n",
       "[Step 737] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 738] Action: [Move to LEFT ARM]\n",
@@ -1707,7 +1676,7 @@
       "[Step 740] Action: [Move to LEFT ARM]\n",
       "[Step 740] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 741] Action: [Move to LEFT ARM]\n",
-      "[Step 741] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 741] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 742] Action: [Move to LEFT ARM]\n",
       "[Step 742] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 743] Action: [Move to LEFT ARM]\n",
@@ -1719,13 +1688,13 @@
       "[Step 746] Action: [Move to LEFT ARM]\n",
       "[Step 746] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 747] Action: [Move to LEFT ARM]\n",
-      "[Step 747] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 747] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 748] Action: [Move to LEFT ARM]\n",
       "[Step 748] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 749] Action: [Move to LEFT ARM]\n",
-      "[Step 749] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 749] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 750] Action: [Move to LEFT ARM]\n",
-      "[Step 750] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 750] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 751] Action: [Move to LEFT ARM]\n",
       "[Step 751] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 752] Action: [Move to LEFT ARM]\n",
@@ -1733,7 +1702,7 @@
       "[Step 753] Action: [Move to LEFT ARM]\n",
       "[Step 753] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 754] Action: [Move to LEFT ARM]\n",
-      "[Step 754] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 754] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 755] Action: [Move to LEFT ARM]\n",
       "[Step 755] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 756] Action: [Move to LEFT ARM]\n",
@@ -1743,15 +1712,15 @@
       "[Step 758] Action: [Move to LEFT ARM]\n",
       "[Step 758] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 759] Action: [Move to LEFT ARM]\n",
-      "[Step 759] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 759] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 760] Action: [Move to LEFT ARM]\n",
-      "[Step 760] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 760] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 761] Action: [Move to LEFT ARM]\n",
-      "[Step 761] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 761] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 762] Action: [Move to LEFT ARM]\n",
       "[Step 762] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 763] Action: [Move to LEFT ARM]\n",
-      "[Step 763] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 763] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 764] Action: [Move to LEFT ARM]\n",
       "[Step 764] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 765] Action: [Move to LEFT ARM]\n",
@@ -1781,13 +1750,13 @@
       "[Step 777] Action: [Move to LEFT ARM]\n",
       "[Step 777] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 778] Action: [Move to LEFT ARM]\n",
-      "[Step 778] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 778] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 779] Action: [Move to LEFT ARM]\n",
       "[Step 779] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 780] Action: [Move to LEFT ARM]\n",
       "[Step 780] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 781] Action: [Move to LEFT ARM]\n",
-      "[Step 781] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 781] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 782] Action: [Move to LEFT ARM]\n",
       "[Step 782] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 783] Action: [Move to LEFT ARM]\n",
@@ -1801,7 +1770,7 @@
       "[Step 787] Action: [Move to LEFT ARM]\n",
       "[Step 787] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 788] Action: [Move to LEFT ARM]\n",
-      "[Step 788] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 788] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 789] Action: [Move to LEFT ARM]\n",
       "[Step 789] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 790] Action: [Move to LEFT ARM]\n",
@@ -1809,9 +1778,9 @@
       "[Step 791] Action: [Move to LEFT ARM]\n",
       "[Step 791] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 792] Action: [Move to LEFT ARM]\n",
-      "[Step 792] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 792] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 793] Action: [Move to LEFT ARM]\n",
-      "[Step 793] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 793] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 794] Action: [Move to LEFT ARM]\n",
       "[Step 794] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 795] Action: [Move to LEFT ARM]\n",
@@ -1819,7 +1788,7 @@
       "[Step 796] Action: [Move to LEFT ARM]\n",
       "[Step 796] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 797] Action: [Move to LEFT ARM]\n",
-      "[Step 797] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 797] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 798] Action: [Move to LEFT ARM]\n",
       "[Step 798] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 799] Action: [Move to LEFT ARM]\n",
@@ -1835,7 +1804,7 @@
       "[Step 804] Action: [Move to LEFT ARM]\n",
       "[Step 804] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 805] Action: [Move to LEFT ARM]\n",
-      "[Step 805] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 805] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 806] Action: [Move to LEFT ARM]\n",
       "[Step 806] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 807] Action: [Move to LEFT ARM]\n",
@@ -1861,17 +1830,17 @@
       "[Step 817] Action: [Move to LEFT ARM]\n",
       "[Step 817] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 818] Action: [Move to LEFT ARM]\n",
-      "[Step 818] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 818] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 819] Action: [Move to LEFT ARM]\n",
       "[Step 819] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 820] Action: [Move to LEFT ARM]\n",
-      "[Step 820] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 820] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 821] Action: [Move to LEFT ARM]\n",
       "[Step 821] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 822] Action: [Move to LEFT ARM]\n",
-      "[Step 822] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 822] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 823] Action: [Move to LEFT ARM]\n",
-      "[Step 823] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 823] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 824] Action: [Move to LEFT ARM]\n",
       "[Step 824] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 825] Action: [Move to LEFT ARM]\n",
@@ -1879,15 +1848,15 @@
       "[Step 826] Action: [Move to LEFT ARM]\n",
       "[Step 826] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 827] Action: [Move to LEFT ARM]\n",
-      "[Step 827] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 827] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 828] Action: [Move to LEFT ARM]\n",
-      "[Step 828] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 828] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 829] Action: [Move to LEFT ARM]\n",
-      "[Step 829] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 829] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 830] Action: [Move to LEFT ARM]\n",
       "[Step 830] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 831] Action: [Move to LEFT ARM]\n",
-      "[Step 831] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 831] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 832] Action: [Move to LEFT ARM]\n",
       "[Step 832] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 833] Action: [Move to LEFT ARM]\n",
@@ -1909,9 +1878,9 @@
       "[Step 841] Action: [Move to LEFT ARM]\n",
       "[Step 841] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 842] Action: [Move to LEFT ARM]\n",
-      "[Step 842] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 842] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 843] Action: [Move to LEFT ARM]\n",
-      "[Step 843] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 843] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 844] Action: [Move to LEFT ARM]\n",
       "[Step 844] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 845] Action: [Move to LEFT ARM]\n",
@@ -1921,9 +1890,9 @@
       "[Step 847] Action: [Move to LEFT ARM]\n",
       "[Step 847] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 848] Action: [Move to LEFT ARM]\n",
-      "[Step 848] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 848] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 849] Action: [Move to LEFT ARM]\n",
-      "[Step 849] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 849] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 850] Action: [Move to LEFT ARM]\n",
       "[Step 850] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 851] Action: [Move to LEFT ARM]\n",
@@ -1943,7 +1912,7 @@
       "[Step 858] Action: [Move to LEFT ARM]\n",
       "[Step 858] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 859] Action: [Move to LEFT ARM]\n",
-      "[Step 859] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 859] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 860] Action: [Move to LEFT ARM]\n",
       "[Step 860] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 861] Action: [Move to LEFT ARM]\n",
@@ -1955,9 +1924,9 @@
       "[Step 864] Action: [Move to LEFT ARM]\n",
       "[Step 864] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 865] Action: [Move to LEFT ARM]\n",
-      "[Step 865] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 865] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 866] Action: [Move to LEFT ARM]\n",
-      "[Step 866] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 866] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 867] Action: [Move to LEFT ARM]\n",
       "[Step 867] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 868] Action: [Move to LEFT ARM]\n",
@@ -1965,23 +1934,23 @@
       "[Step 869] Action: [Move to LEFT ARM]\n",
       "[Step 869] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 870] Action: [Move to LEFT ARM]\n",
-      "[Step 870] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 870] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 871] Action: [Move to LEFT ARM]\n",
-      "[Step 871] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 871] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 872] Action: [Move to LEFT ARM]\n",
       "[Step 872] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 873] Action: [Move to LEFT ARM]\n",
       "[Step 873] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 874] Action: [Move to LEFT ARM]\n",
-      "[Step 874] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 874] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 875] Action: [Move to LEFT ARM]\n",
-      "[Step 875] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 875] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 876] Action: [Move to LEFT ARM]\n",
       "[Step 876] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 877] Action: [Move to LEFT ARM]\n",
       "[Step 877] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 878] Action: [Move to LEFT ARM]\n",
-      "[Step 878] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 878] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 879] Action: [Move to LEFT ARM]\n",
       "[Step 879] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 880] Action: [Move to LEFT ARM]\n",
@@ -1995,7 +1964,7 @@
       "[Step 884] Action: [Move to LEFT ARM]\n",
       "[Step 884] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 885] Action: [Move to LEFT ARM]\n",
-      "[Step 885] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 885] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 886] Action: [Move to LEFT ARM]\n",
       "[Step 886] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 887] Action: [Move to LEFT ARM]\n",
@@ -2003,11 +1972,11 @@
       "[Step 888] Action: [Move to LEFT ARM]\n",
       "[Step 888] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 889] Action: [Move to LEFT ARM]\n",
-      "[Step 889] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 889] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 890] Action: [Move to LEFT ARM]\n",
       "[Step 890] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 891] Action: [Move to LEFT ARM]\n",
-      "[Step 891] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 891] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 892] Action: [Move to LEFT ARM]\n",
       "[Step 892] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 893] Action: [Move to LEFT ARM]\n",
@@ -2037,7 +2006,7 @@
       "[Step 905] Action: [Move to LEFT ARM]\n",
       "[Step 905] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 906] Action: [Move to LEFT ARM]\n",
-      "[Step 906] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 906] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 907] Action: [Move to LEFT ARM]\n",
       "[Step 907] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 908] Action: [Move to LEFT ARM]\n",
@@ -2047,15 +2016,15 @@
       "[Step 910] Action: [Move to LEFT ARM]\n",
       "[Step 910] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 911] Action: [Move to LEFT ARM]\n",
-      "[Step 911] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 911] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 912] Action: [Move to LEFT ARM]\n",
       "[Step 912] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 913] Action: [Move to LEFT ARM]\n",
       "[Step 913] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 914] Action: [Move to LEFT ARM]\n",
-      "[Step 914] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 914] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 915] Action: [Move to LEFT ARM]\n",
-      "[Step 915] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 915] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 916] Action: [Move to LEFT ARM]\n",
       "[Step 916] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 917] Action: [Move to LEFT ARM]\n",
@@ -2065,7 +2034,7 @@
       "[Step 919] Action: [Move to LEFT ARM]\n",
       "[Step 919] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 920] Action: [Move to LEFT ARM]\n",
-      "[Step 920] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 920] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 921] Action: [Move to LEFT ARM]\n",
       "[Step 921] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 922] Action: [Move to LEFT ARM]\n",
@@ -2077,17 +2046,17 @@
       "[Step 925] Action: [Move to LEFT ARM]\n",
       "[Step 925] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 926] Action: [Move to LEFT ARM]\n",
-      "[Step 926] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 926] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 927] Action: [Move to LEFT ARM]\n",
       "[Step 927] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 928] Action: [Move to LEFT ARM]\n",
       "[Step 928] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 929] Action: [Move to LEFT ARM]\n",
-      "[Step 929] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 929] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 930] Action: [Move to LEFT ARM]\n",
       "[Step 930] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 931] Action: [Move to LEFT ARM]\n",
-      "[Step 931] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 931] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 932] Action: [Move to LEFT ARM]\n",
       "[Step 932] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 933] Action: [Move to LEFT ARM]\n",
@@ -2097,27 +2066,27 @@
       "[Step 935] Action: [Move to LEFT ARM]\n",
       "[Step 935] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 936] Action: [Move to LEFT ARM]\n",
-      "[Step 936] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 936] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 937] Action: [Move to LEFT ARM]\n",
-      "[Step 937] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 937] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 938] Action: [Move to LEFT ARM]\n",
       "[Step 938] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 939] Action: [Move to LEFT ARM]\n",
       "[Step 939] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 940] Action: [Move to LEFT ARM]\n",
-      "[Step 940] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 940] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 941] Action: [Move to LEFT ARM]\n",
       "[Step 941] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 942] Action: [Move to LEFT ARM]\n",
-      "[Step 942] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 942] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 943] Action: [Move to LEFT ARM]\n",
       "[Step 943] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 944] Action: [Move to LEFT ARM]\n",
       "[Step 944] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 945] Action: [Move to LEFT ARM]\n",
-      "[Step 945] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 945] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 946] Action: [Move to LEFT ARM]\n",
-      "[Step 946] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 946] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 947] Action: [Move to LEFT ARM]\n",
       "[Step 947] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 948] Action: [Move to LEFT ARM]\n",
@@ -2137,29 +2106,29 @@
       "[Step 955] Action: [Move to LEFT ARM]\n",
       "[Step 955] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 956] Action: [Move to LEFT ARM]\n",
-      "[Step 956] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 956] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 957] Action: [Move to LEFT ARM]\n",
       "[Step 957] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 958] Action: [Move to LEFT ARM]\n",
       "[Step 958] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 959] Action: [Move to LEFT ARM]\n",
-      "[Step 959] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 959] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 960] Action: [Move to LEFT ARM]\n",
-      "[Step 960] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 960] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 961] Action: [Move to LEFT ARM]\n",
-      "[Step 961] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 961] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 962] Action: [Move to LEFT ARM]\n",
       "[Step 962] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 963] Action: [Move to LEFT ARM]\n",
       "[Step 963] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 964] Action: [Move to LEFT ARM]\n",
-      "[Step 964] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 964] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 965] Action: [Move to LEFT ARM]\n",
       "[Step 965] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 966] Action: [Move to LEFT ARM]\n",
       "[Step 966] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 967] Action: [Move to LEFT ARM]\n",
-      "[Step 967] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 967] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 968] Action: [Move to LEFT ARM]\n",
       "[Step 968] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 969] Action: [Move to LEFT ARM]\n",
@@ -2167,13 +2136,13 @@
       "[Step 970] Action: [Move to LEFT ARM]\n",
       "[Step 970] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 971] Action: [Move to LEFT ARM]\n",
-      "[Step 971] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 971] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 972] Action: [Move to LEFT ARM]\n",
       "[Step 972] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 973] Action: [Move to LEFT ARM]\n",
       "[Step 973] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 974] Action: [Move to LEFT ARM]\n",
-      "[Step 974] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 974] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 975] Action: [Move to LEFT ARM]\n",
       "[Step 975] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 976] Action: [Move to LEFT ARM]\n",
@@ -2187,9 +2156,9 @@
       "[Step 980] Action: [Move to LEFT ARM]\n",
       "[Step 980] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 981] Action: [Move to LEFT ARM]\n",
-      "[Step 981] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 981] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 982] Action: [Move to LEFT ARM]\n",
-      "[Step 982] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 982] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 983] Action: [Move to LEFT ARM]\n",
       "[Step 983] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 984] Action: [Move to LEFT ARM]\n",
@@ -2197,7 +2166,7 @@
       "[Step 985] Action: [Move to LEFT ARM]\n",
       "[Step 985] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 986] Action: [Move to LEFT ARM]\n",
-      "[Step 986] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 986] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 987] Action: [Move to LEFT ARM]\n",
       "[Step 987] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 988] Action: [Move to LEFT ARM]\n",
@@ -2205,15 +2174,15 @@
       "[Step 989] Action: [Move to LEFT ARM]\n",
       "[Step 989] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 990] Action: [Move to LEFT ARM]\n",
-      "[Step 990] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 990] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 991] Action: [Move to LEFT ARM]\n",
-      "[Step 991] Observation: [LEFT ARM,  Loss!, Null]\n",
+      "[Step 991] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 992] Action: [Move to LEFT ARM]\n",
       "[Step 992] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 993] Action: [Move to LEFT ARM]\n",
       "[Step 993] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 994] Action: [Move to LEFT ARM]\n",
-      "[Step 994] Observation: [LEFT ARM,  Reward!, Null]\n",
+      "[Step 994] Observation: [LEFT ARM,  Loss!, Null]\n",
       "[Step 995] Action: [Move to LEFT ARM]\n",
       "[Step 995] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 996] Action: [Move to LEFT ARM]\n",
@@ -2223,7 +2192,7 @@
       "[Step 998] Action: [Move to LEFT ARM]\n",
       "[Step 998] Observation: [LEFT ARM,  Reward!, Null]\n",
       "[Step 999] Action: [Move to LEFT ARM]\n",
-      "[Step 999] Observation: [LEFT ARM,  Reward!, Null]\n"
+      "[Step 999] Observation: [LEFT ARM,  Loss!, Null]\n"
      ]
     }
    ],
@@ -2267,14 +2236,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 12,
    "metadata": {
     "scrolled": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -2286,7 +2255,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -2298,7 +2267,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -2310,7 +2279,7 @@
     },
     {
      "data": {
-      "image/png": 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qrur7/0vsL2ladndfaKGlCIreApxP05z5AeC02RlVdR3Nl+ShNNcvL6fppDvXWch8Xtym/WngOzRnRWs68z9GE/ScNc84NF8Ch7b/vwF4FwtomzqfCPwezZfSE2k64M23/Kk0rVFvpzmY3g3crk3nCTRfapcDfw88taq+skiZu/k+JU1T+/8Z839m8/Remj47ZwFfobnUCE2LGSy+XRfyQpp9/hma/jKv4sYtbwBPo2lePY9mO76DG1oSHwJsSnOX4btp+kRcPEc5rqTpYPtWmjPBb7Nj0/i8FtuPVfUp4PdpttOVNJ1qnzZO2h1999HY230p6lVVXUZzyeY17f/elaZ1tXf5JlC/u2l9j+bH7Zx2XQ9aZPmraOrhe2jqxJNoAr7Z+V+kOc4vatOb6xLlm4CfT3OH0jvHyOMu1Zf2ktRj2/+5lKYe/wU73hF5FvDNqrq0Hf8YzQ/z59o0Fiz3POt9L82l64+1ef7gIlmdLdOXaQKU57XpfAA4oV33pTR1Z9yWlH+k+VH+As3lloW29wdpvrMuS9MKsoNdzMdC7kJzjH2Xpk/Xh1j4TqwzaPqvzA5/0k7v3vU4O/zaBPI36xnAe6pqS1V9Y3YA/g44IvO32LwG+P3McUddVX28U+cWNVsumjp8CE1/wa73j5R/9HEAO+vlI+ku9FuwgeZqxTELLNN0OtLKk+ZW18/SdPhb6OxHkqQVwdd8rCBJnphk9yQ/Q9OU+O8GRJIkNQyKVpbn0lzW2EpzK+O8D86UJGml8fKZeklyL5o+I7Odoi+huUvh/OnlSpKkXWdLkcaW5KU0HedD0zH40+3nU5McO828SZK0q2wp0tiSfJnmydU/Hpm+O7Clqua9Wy3JWppnY/CGN7zhkLVr1y5pXiUNxlx3so7t+M77FxddtmqX1qWbP9+YrD5+wsjTY1v7sfDzO6iq9cD62dHJZ02SpF1jUKQ+XgB8OMlXuOER/Xelec/Munn/az7XXDG5nN3c7HnDQ7iPz8o+OT2+01pdX/vAFHMyfTmw87L4lXx8wA7HyK6wj4j6MCjS2KrqA0nuQfPgy25H602147u9JOkmYWbaGdDNikGRemmfa/SpaedDksZhS5H6MCiSJA3Wyr44rb4MiiRJg2VLkfowKJIkDZYtRerDoEiSNFi2FKkPgyJJ0mB595n6MIiWJA3Wqh7DOJIcnuSCJFvner1Rkrsm+WiS/07y+SS/MpGCaFkYFEmSBmuSQVGSGeBE4HHAwcBTkhw8stifAKdX1QOAo4DXT6AYWiYGRZKkwUqPYQyHAlur6sKqupbmBdlHjixTwG3az/sAX9+lAmhZGRRJkgarT0tRkrVJNneG0TdX788NrzgC2M4NT/efdTzwtCTbgY3A8yZbIi0lO1pLkgarT0frkRdX76ynAG+pqr9J8gvAvya5T/s2AN3EGRRJkgZrwpdDLgFWd8YPaKd1HQMcDlBVn0yyJ3B74JuTzYqWgpfPJEmDNeE+RZuANUkOSrI7TUfqDSPLXAw8CiDJzwF7At/axWJomdhSJEkarEme+VfVdUnWAWfQXJk7qaq2JDkB2FxVG4AXA29M8kKaTtdHV1VNMBtaQgZFkqTBmvTlkKraSNOBujvtuM7n84CHTni1WiYGRZKkwfLdZ+rDoEiSNFj+yKkP64skabBsKVIfBkWSpMHyFmv1YVAkSRosW4rUh0GRJGmwbClSHwZFkqTB6vOaD8mgSJI0WLYUqQ+DIknSYBkUqQ+DIknSYNnRWn0YFEmSBiurDIs0PoMiSdJgJQZFGp9BkSRpsGZm7FWk8RkUSZIGy8tn6sOgSJI0WF4+Ux8GRZKkwbKlSH0YFEmSBsuWIvVhDzRJ0mBlVcYexkovOTzJBUm2Jjl2jvmvS3JuO3w5yVUTL5SWjC1FkqTBmuTdZ0lmgBOBRwPbgU1JNlTVebPLVNULO8s/D3jAxDKgJWdLkSRpsJKMPYzhUGBrVV1YVdcCpwFHLrD8U4BTJ1AMLRODIknSYPW5fJZkbZLNnWHtSHL7A9s649vbaTdeb3IgcBDwkaUpmZaCl88kSYPVp6N1Va0H1k9o1UcB76yq6yeUnpaBQZEkabAmfEv+JcDqzvgB7bS5HAU8d5Ir19IzKJIkDdaqyb7mYxOwJslBNMHQUcBTRxdKci/gdsAnJ7lyLT2DIknSYE3yOUVVdV2SdcAZwAxwUlVtSXICsLmqNrSLHgWcVlU1sZVrWRgUSZIGa9WEn2hdVRuBjSPTjhsZP36iK9WyMSiSJA2WT7RWHwZFkqTB8t1n6sOgSJI0WLYUqQ+DIknSYK2aMSjS+AyKJEmD5eUz9WFQJEkarFVePlMPBkWSpMGypUh9GBRJkgbLjtbqw6BIkjRYthSpD4MiSdJgTfjdZxo4gyJJ0mB5+Ux9GBRJkgYrq2wp0vgMiiRJg2WfIvVhUCRJGi4vn6kHgyJJ0mCtusXMtLOgmxGDIknSYNnRWn3YA02SNFyrMv4whiSHJ7kgydYkx86zzG8mOS/JliSnTLQ8WlK2FEmSBmuSd58lmQFOBB4NbAc2JdlQVed1llkDvAx4aFVdmeSOE8uAlpwtRZKkwUoy9jCGQ4GtVXVhVV0LnAYcObLM7wEnVtWVAFX1zYkWSEvKoEiSNFhZlfGHZG2SzZ1h7Uhy+wPbOuPb22ld9wDukeQTST6V5PClLJ8my8tnkqTBysz4d59V1Xpg/S6u8hbAGuARwAHAWUnuW1VX7WK6WgYGRZKkwZrwwxsvAVZ3xg9op3VtB86pqh8D/5PkyzRB0qZJZkRLw8tnkqTB6nP5bAybgDVJDkqyO3AUsGFkmX+jaSUiye1pLqddOLkSaSnZUiRJGq5M7ty/qq5Lsg44A5gBTqqqLUlOADZX1YZ23mOSnAdcD7ykqq6YWCa0pAyKJEmDNel3n1XVRmDjyLTjOp8LeFE76GbGoEiSNFi+EFZ9GBRJkgarz91nkkGRJGmwbClSHwZFkqTB8oWw6sOgSJI0WJN895mGz6BIkjRYXj5THwZFkqTByowtRRqfQZEkabC8fKY+DIokSYNlR2v1YVAkSRou+xSpB4MiSdJgeflMfRgUSZIGy8tn6sOgSJI0WN59pj4MiiRJg+VzitSHQZEkabiMidSDQZEkabjsU6QeDIokSYNlTKQ+7IEmSRqszGTsYaz0ksOTXJBka5Jj55h/dJJvJTm3HZ458UJpydhSJEkargk2FSWZAU4EHg1sBzYl2VBV540s+vaqWjexFWvZ2FIkSRquVT2GxR0KbK2qC6vqWuA04MjJZ1rTYlAkSRqsJH2GtUk2d4a1I8ntD2zrjG9vp4369SSfT/LOJKuXrHCaOC+fSZKGq8fls6paD6zfxTW+Fzi1qn6U5FnAW4FH7mKaWia2FEmSBisZfxjDJUC35eeAdtpPVdUVVfWjdvRNwCGTKIeWh0GRJGm4ZjL+sLhNwJokByXZHTgK2NBdIMl+ndEjgPMnVhYtOS+fSZIGa5IvhK2q65KsA84AZoCTqmpLkhOAzVW1AfiDJEcA1wHfBo6eWAa05AyKJEnDNeGHN1bVRmDjyLTjOp9fBrxssmvVcjEokiQNli+EVR8GRZKk4TImUg8GRZKk4fLlZ+rBoEiSNFjjvtNMAoMiSdKA2VCkPgyKJEnDZVSkHgyKJEmDZUykPgyKJEnD5S356sGgSJI0WD6nSH0YFEmShsvrZ+rBoEiSNFjxtefqwaBI07PnvtPOwU3C8VXTzsJNRg48fNpZuOnw+JgMW4rUgzG0JibJ70w7D5K0g/QYtOIZFGmSXjHfjCRrk2xOsnn9+vXLmSdJK1iSsQfJy2fqJcnn55sF3Gm+/6uq9cBsNOT1IknLY8Zzf43PoEh93Ql4LHDlyPQA/9UrpWuumFCWboY6/UXqax+YYkamr9uP6PgVfra+Q/+ylXx8wOT6VHlLvnowhFZf7wP2qqqvjQwXAWdON2uSNCKrxh/GSS45PMkFSbYmOXaB5X49SSV50MTKoiVnS5F6qapjFpj31OXMiyQtaoKtj0lmgBOBRwPbgU1JNlTVeSPL7Q08HzhnYivXsrClSJI0XKsy/rC4Q4GtVXVhVV0LnAYcOcdyfw78FXDN5Aqi5WBQJEkarh6Xz7p3ybbD2pHU9ge2dca3t9NuWF3yQGB1Vf3HEpdMS8DLZ5Kk4epx99nIXbK9JVkFvBY4emfT0HQZFEmShmvVRC+IXAKs7owf0E6btTdwH+DM9rlHdwY2JDmiqjZPMiNaGgZFkqThmuxjHjYBa5IcRBMMHQX89AaTqvoOcPsbVp0zgT80ILr5MCiSJA3XBFuKquq6JOuAM4AZ4KSq2pLkBGBzVW2Y2Mo0FQZFkqThmvADQatqI7BxZNpx8yz7iImuXEvOoEiSNFwzM9POgW5GDIokScO1wl8do34MiiRJgxXffaYeDIokScM15jvNJDAokiQNmS1F6sGgSJI0XPYpUg8GRZKk4fLuM/VgUCRJGi5bitSDQZEkabgm++4zDZxBkSRpuGwpUg8GRZKk4fLuM/VgUCRJGi6fU6QeDIokScM1Y1Ck8RkUSZKGy47W6sGgSJI0XHa0Vg8GRZKk4TIoUg8GRZKk4bKjtXqwtkiShmtVxh/GkOTwJBck2Zrk2DnmPzvJF5Kcm+TsJAdPvExaMgZFkqThSsYfFk0qM8CJwOOAg4GnzBH0nFJV962q+wOvBl476SJp6RgUSZKGa4JBEXAosLWqLqyqa4HTgCO7C1TVdzujtwZqYmXRkrNPkSRpwMbvaJ1kLbC2M2l9Va3vjO8PbOuMbwceMkc6zwVeBOwOPLJPbjVdBkWSpOHqcfNZGwCtX3TBxdM5ETgxyVOBPwGesatpanl4+UySNFyTvXx2CbC6M35AO20+pwG/tgu51zIzKJIkDdeqVeMPi9sErElyUJLdgaOADd0FkqzpjP4q8JWJlUVLzstnkqQBm9zDG6vquiTrgDOAGeCkqtqS5ARgc1VtANYlOQz4MXAlXjq7WTEokiQN14QfaF1VG4GNI9OO63x+/mTXqOVkUCRJGi5f86EeDIokScNlUKQeDIokScPlu8/Ug0GRJGm4bClSDwZFkqThMiZSDwZFkqThsqVIPRgUSZIGzKBI4zMokiQNly1F6sGgSJI0XKsMijQ+gyJJ0nDZUqQeDIokSQNmUKTxGRRJkobLliL1YFAkSRougyL1YFAkSRougyL1YFAkSRougyL1YFAkSRougyL14OuDJUnDlYw/jJVcDk9yQZKtSY6dY/6LkpyX5PNJPpzkwImXSUvGoEiSNGDpMSySUjIDnAg8DjgYeEqSg0cW+2/gQVV1P+CdwKsnUgwtC4MiSdJwTbal6FBga1VdWFXXAqcBR3YXqKqPVtUP2tFPAQdMtDxaUvYpkiQNV2Ymmdr+wLbO+HbgIQssfwzw/klmQEvLoEiSNFw9OlonWQus7UxaX1Xrd261eRrwIODhO/P/mg6DIknScGX8XiJtALRQEHQJsLozfkA7bcdVJocBfww8vKp+NHYGNHX2KZIkDdjkOloDm4A1SQ5KsjtwFLBhh7UlDwDeABxRVd+cUCG0TGwpkiQN1wSfU1RV1yVZB5wBzAAnVdWWJCcAm6tqA/AaYC/gHWnWfXFVHTGxTGhJGRRJkgZsshdEqmojsHFk2nGdz4dNdIVaVgZFkqThWmUvEY3PoEiSNGC+5kPjMyiSJA1Xj7vPJIMiSdJw+UJY9WBQJEkaMIMijc+gSJI0XF4+Uw8GRZKkwYpBkXowKJIkDZdBkXowKJIkDZh9ijQ+gyJJ0nB595l6MCiSJA2Xl8/Ug0GRJGm4DIrUg0GRJGm4DIrUg0GRJGnA7FOk8RkUSZKGy47W6sGgSJI0YF4+0/gMiiRJw2VLkXowhJYkDVdmxh/GSS45PMkFSbYmOXaO+Q9L8tkk1yV50sTLoyVlUCRJGq5k/GHRpDIDnAg8DjgYeEqSg0cWuxg4GjhlwiXRMvDymSRpwCZ6+exQYGtVXQiQ5DTgSOC82QWq6qJ23k8muWItD1uKJEnD1aOlKMnaJJs7w9qR1PYHtnXGt7fTNBC2FEmSBmz8lqKqWg+sX7q86KbOoEiSNFyTvfvsEmB1Z/yAdpoGwqBIkjRcY3/pXKEAAAQbSURBVN5VNqZNwJokB9EEQ0cBT53kCjRd9imSJA1YegwLq6rrgHXAGcD5wOlVtSXJCUmOAEjy4CTbgd8A3pBky8SLpCVjS5Ekabgm/PDGqtoIbByZdlzn8yaay2q6GTIokiQNmE+01vgMiiRJw+VrPtSDQZEkabhi11mNz6BIkjRgBkUan0GRJGm4vHymHgyKJEkDZlCk8RkUSZIGzKBI4zMokiQNVrx8ph4MiiRJw+XdZ+rBoEiSNGC2FGl8BkWSpOGypUg9GBRJkgbMliKNz6BIkjRcdrRWDwZFkqQBMyjS+AyKJEnDZZ8i9WBQJEkaLi+fqQeDIknSgBkUaXy2K0qShiurxh/GSS45PMkFSbYmOXaO+XskeXs7/5wkd5twibSEUlXTzoNWHiudpHHtWlPPD781/vfNLe+w4LqSzABfBh4NbAc2AU+pqvM6yzwHuF9VPTvJUcATq+rJO5N1LT9biiRJwzXZlqJDga1VdWFVXQucBhw5ssyRwFvbz+8EHhVfwHazYZ8iLbskz6qq9dPOx01BkrVui4bb4gZuiwnac9+xA5Ika4G1nUnrR/bD/sC2zvh24CEjyfx0maq6Lsl3gH2By/tkW9NhS5GmYe3ii6wYbosbuC1u4LaYgqpaX1UP6gwGpiuMQZEkSeO5BFjdGT+gnTbnMkluAewDXLEsudMuMyiSJGk8m4A1SQ5KsjtwFLBhZJkNwDPaz08CPlLe0XSzYZ8iTYNN0jdwW9zAbXEDt8VNUNtHaB1wBjADnFRVW5KcAGyuqg3Am4F/TbIV+DZN4KSbCW/JlyRJwstnkiRJgEGRJEkSYFCkZbTY4/FXkiQnJflmki9OOy/TlGR1ko8mOS/JliTPn3aepiXJnkk+neRz7bZ4xbTzJK009inSshjn8fgrSZKHAVcD/1JV95l2fqYlyX7AflX12SR7A58Bfm0l1ov2qce3rqqrk+wGnA08v6o+NeWsSSuGLUVaLuM8Hn/FqKqzaO5MWdGq6tKq+mz7+XvA+TRPBF5xqnF1O7pbO3jWKi0jgyItl7kej78if/w0t/Zt4g8AzpluTqYnyUySc4FvAh+sqhW7LaRpMCiSNHVJ9gLeBbygqr477fxMS1VdX1X3p3lS8qFJVuylVWkaDIq0XMZ5PL5WoLb/zLuAt1XVu6edn5uCqroK+Chw+LTzIq0kBkVaLuM8Hl8rTNu5+M3A+VX12mnnZ5qS3CHJbdvPt6S5KeFL082VtLIYFGlZVNV1wOzj8c8HTq+qLdPN1fQkORX4JHDPJNuTHDPtPE3JQ4HfBh6Z5Nx2+JVpZ2pK9gM+muTzNCcRH6yq9005T9KK4i35kiRJ2FIkSZIEGBRJkiQBBkWSJEmAQZEkSRJgUCRJkgQYFEmSJAEGRZIkSQD8f3eruXvP9w2XAAAAAElFTkSuQmCC",
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",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -2331,12 +2300,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -2348,7 +2317,7 @@
     },
     {
      "data": {
-      "image/png": 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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 432x288 with 2 Axes>"
       ]
@@ -2366,11 +2335,9 @@
   }
  ],
  "metadata": {
-  "interpreter": {
-   "hash": "24ee14d9f6452059a99d44b6cbd71d1bb479b0539b0360a6a17428ecea9f0810"
-  },
   "kernelspec": {
-   "display_name": "Python 3.8.10 64-bit ('pymdp_env2': conda)",
+   "display_name": "Python 3.8.8 ('base')",
+   "language": "python",
    "name": "python3"
   },
   "language_info": {
@@ -2383,7 +2350,12 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.8.8"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "70b7ceca5df5387258d861d4588082cea9500e731be001548c95afd8cd8c3af8"
+   }
   }
  },
  "nbformat": 4,
diff --git a/pymdp/utils.py b/pymdp/utils.py
index 18a5a69e..93e75cfd 100644
--- a/pymdp/utils.py
+++ b/pymdp/utils.py
@@ -8,6 +8,8 @@
 
 import numpy as np
 import pandas as pd
+import seaborn as sns
+import matplotlib.pyplot as plt
 
 import warnings
 import itertools
@@ -616,6 +618,31 @@ def build_xn_vn_array(xn):
     
     return xn_array
 
+def plot_beliefs(belief_dist, title=""):
+    """
+    Utility function that plots a bar chart of a categorical probability distribution,
+    with each bar height corresponding to the probability of one of the elements of the categorical
+    probability vector.
+    """
+
+    plt.grid(zorder=0)
+    plt.bar(range(belief_dist.shape[0]), belief_dist, color='r', zorder=3)
+    plt.xticks(range(belief_dist.shape[0]))
+    plt.title(title)
+    plt.show()
+    
+def plot_likelihood(A, title=""):
+    """
+    Utility function that shows a heatmap of a 2-D likelihood (hidden causes in the columns, observations in the rows),
+    with hotter colors indicating higher probability.
+    """
+
+    ax = sns.heatmap(A, cmap="OrRd", linewidth=2.5)
+    plt.xticks(range(A.shape[1]+1))
+    plt.yticks(range(A.shape[0]+1))
+    plt.title(title)
+    plt.show()
+
 
     
    


Test patch:
diff --git a/test/test_demos.py b/test/test_demos.py
index 0b2a5aa1..35d98c79 100644
--- a/test/test_demos.py
+++ b/test/test_demos.py
@@ -5,6 +5,7 @@
 import matplotlib.pyplot as plt
 
 from pymdp.agent import Agent
+from pymdp.utils import plot_beliefs, plot_likelihood
 from pymdp import utils, maths, default_models
 from pymdp import control
 from pymdp.envs import TMazeEnv, TMazeEnvNullOutcome
@@ -63,18 +64,6 @@ def test_tmaze_demo(self):
         This unit test runs the a concise version of the code in the `tmaze_demo.ipynb` tutorial notebook to make sure it works if things are changed
         """
 
-        def plot_beliefs(belief_dist, title=""):
-            plt.grid(zorder=0)
-            plt.bar(range(belief_dist.shape[0]), belief_dist, color='r', zorder=3)
-            plt.xticks(range(belief_dist.shape[0]))
-            plt.title(title)
-            
-        def plot_likelihood(A, title=""):
-            ax = sns.heatmap(A, cmap="OrRd", linewidth=2.5)
-            plt.xticks(range(A.shape[1]))
-            plt.yticks(range(A.shape[0]))
-            plt.title(title)
-
         reward_probabilities = [0.98, 0.02] # probabilities used in the original SPM T-maze demo
         env = TMazeEnv(reward_probs = reward_probabilities)
 
@@ -132,18 +121,6 @@ def test_tmaze_learning_demo(self):
         """
         This unit test runs the a concise version of the code in the `tmaze_demo_learning.ipynb` tutorial notebook to make sure it works if things are changed
         """
-
-        def plot_beliefs(belief_dist, title=""):
-            plt.grid(zorder=0)
-            plt.bar(range(belief_dist.shape[0]), belief_dist, color='r', zorder=3)
-            plt.xticks(range(belief_dist.shape[0]))
-            plt.title(title)
-            
-        def plot_likelihood(A, title=""):
-            ax = sns.heatmap(A, cmap="OrRd", linewidth=2.5)
-            plt.xticks(range(A.shape[1]))
-            plt.yticks(range(A.shape[0]))
-            plt.title(title)
         
         reward_probabilities = [0.85, 0.15] # the 'true' reward probabilities 
         env = TMazeEnvNullOutcome(reward_probs = reward_probabilities)
@@ -228,10 +205,6 @@ def test_gridworld_genmodel_construction(self):
         A = np.eye(9)
 
         labels = [state_mapping[i] for i in range(A.shape[1])]
-        def plot_likelihood(A):
-            fig = plt.figure(figsize = (6,6))
-            ax = sns.heatmap(A, xticklabels = labels, yticklabels = labels, cbar = False)
-            plt.title("Likelihood distribution (A)")
 
         plot_likelihood(A)
 
@@ -290,19 +263,9 @@ def test_gridworld_activeinference(self):
         state_mapping = {0: (0,0), 1: (1,0), 2: (2,0), 3: (0,1), 4: (1,1), 5:(2,1), 6: (0,2), 7:(1,2), 8:(2,2)}
 
         A = np.eye(9)
-        def plot_beliefs(Qs, title=""):
-            #values = Qs.values[:, 0]
-            plt.grid(zorder=0)
-            plt.bar(range(Qs.shape[0]), Qs, color='r', zorder=3)
-            plt.xticks(range(Qs.shape[0]))
-            plt.title(title)
-            
+       
         labels = [state_mapping[i] for i in range(A.shape[1])]
-        def plot_likelihood(A):
-            fig = plt.figure(figsize = (6,6))
-            ax = sns.heatmap(A, xticklabels = labels, yticklabels = labels, cbar = False)
-            plt.title("Likelihood distribution (A)")
-            
+       
         def plot_empirical_prior(B):
             fig, axes = plt.subplots(3,2, figsize=(8, 10))
             actions = ['UP', 'RIGHT', 'DOWN', 'LEFT', 'STAY']