Upload PPO LunarLander-v2 trained agent

LunarLander-v2-version_0_0_1.zip

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7916a3ac1492155bc9c481972fea9e9ffade5196da04e56b45d7970ba7bd4ec6
-size 147028
+oid sha256:adb30e22cfec6b1fa0c3b8fa6ec7d637bcc8c3c78f7d6a953f64764bd2d7b051
+size 147024

LunarLander-v2-version_0_0_1/data

@@ -47,7 +47,7 @@
     "_num_timesteps_at_start": 0,
     "seed": null,
     "action_noise": null,
-    "start_time": 1670390697415944315,
+    "start_time": 1670392316716156993,
     "learning_rate": 0.0003,
     "tensorboard_log": null,
     "lr_schedule": {
@@ -56,7 +56,7 @@
     },
     "_last_obs": {
         ":type:": "<class 'numpy.ndarray'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "_last_episode_starts": {
         ":type:": "<class 'numpy.ndarray'>",
@@ -69,13 +69,13 @@
     "_current_progress_remaining": -0.0027007999999999477,
     "ep_info_buffer": {
         ":type:": "<class 'collections.deque'>",
-        ":serialized:": "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"
+        ":serialized:": "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"
     },
     "ep_success_buffer": {
         ":type:": "<class 'collections.deque'>",
         ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="
     },
-    "_n_updates": 2448,
+    "_n_updates": 3672,
     "n_steps": 1024,
     "gamma": 0.99,
     "gae_lambda": 0.98,

LunarLander-v2-version_0_0_1/policy.optimizer.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b71f38f9a8f87773a7af0273e02e8d2e08309c5f187f7d84cce8ad578816b817
+oid sha256:84d0c0aa11cab3c02122ac2081a8dc75a61e443b57123c6ed88317ff5587155c
 size 87865

LunarLander-v2-version_0_0_1/policy.pth

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a6ae79de06cc36e9701592d61e48a2f541243e56f03a6563a278390c37d57e60
+oid sha256:79f08e017b58c6d0d0fa6bc23ce38543243733a0c881c8cc5e0dc19925b107c4
 size 43201

README.md

@@ -16,7 +16,7 @@ model-index:
       type: LunarLander-v2
     metrics:
     - type: mean_reward
-      value: 284.85 +/- 21.90
+      value: 289.38 +/- 20.95
       name: mean_reward
       verified: false
 ---

config.json

@@ -1 +1 @@
-{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__module__": "stable_baselines3.common.policies", "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\n\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param lr_schedule: Learning rate schedule (could be constant)\n    :param net_arch: The specification of the policy and value networks.\n    :param activation_fn: Activation function\n    :param ortho_init: Whether to use or not orthogonal initialization\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\n    :param sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\n    :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n        a positive standard deviation (cf paper). It allows to keep variance\n        above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n    :param squash_output: Whether to squash the output using a tanh function,\n        this allows to ensure boundaries when using gSDE.\n    :param features_extractor_class: Features extractor to use.\n    :param features_extractor_kwargs: Keyword arguments\n        to pass to the features extractor.\n    :param normalize_images: Whether to normalize images or not,\n         dividing by 255.0 (True by default)\n    :param optimizer_class: The optimizer to use,\n        ``th.optim.Adam`` by default\n    :param optimizer_kwargs: Additional keyword arguments,\n        excluding the learning rate, to pass to the optimizer\n    ", "__init__": "<function ActorCriticPolicy.__init__ at 0x7f180eda8c10>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f180eda8ca0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f180eda8d30>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f180eda8dc0>", "_build": "<function ActorCriticPolicy._build at 0x7f180eda8e50>", "forward": "<function ActorCriticPolicy.forward at 0x7f180eda8ee0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f180eda8f70>", "_predict": "<function ActorCriticPolicy._predict at 0x7f180edac040>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f180edac0d0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f180edac160>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f180edac1f0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f180eda58a0>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 2506752, "_total_timesteps": 2500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670390697415944315, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVdQIAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYAAgAAAAAAAGblwbxh1rk/wHetvoJxOD6BuqA8r7BAPQAAAAAAAAAA89acvcNpYrrF57m1HErbsHVJTrs+JAA1AACAPwAAgD8z+RS9rnG3uvbQ7bbCbdqxodAkObbHBzYAAIA/AACAP1olPT79ClI+QpiBvmXnF7/Dzzg9CP0JvgAAAAAAAAAAmmm9uz1wdLsw5Tu9CX+7PHTho7yFW549AACAPwAAgD/TMmo+mVcDP1r6ob7HZiC/lCK2PmZfuL4AAAAAAAAAAOaZIr7cAzq84v52O0Qw4jnzCKo9wjDNugAAgD8AAIA/GpLJvY++Xbo6woE8eyQbNX0bGLnqeiE0AACAPwAAgD/NTBe5fmKnP/GbkrsdOiW/uwVzu03EdzwAAAAAAAAAABpDBD1cUxO6+nwBOGbIHTJmKGO7YwsZtwAAgD8AAIA/M5u9PFdbij819VU99qZyvwP+gj2nNUw9AAAAAAAAAAAzhJi9rsWluooAlrTWk66vDjAmOvV+ZzMAAIA/AACAPwD6eT24/pM4EjBOtGvBYa9Ss1s73biJMwAAgD8AAIA/E1oyPsRFVz86/rU9U4Ahv8Gxtj7mhWA6AAAAAAAAAABmeao8e0qVurNOAbnm5e2zvfqsuhXAFTgAAIA/AACAP2bmS71gzL0/+h70vjTnTD7KWhk8r2+OvQAAAAAAAAAAlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjSUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYksQSwiGlIwBQ5R0lFKULg=="}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0027007999999999477, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVHxAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKUKH2UKIwBcpSMFW51bXB5LmNvcmUubXVsdGlhcnJheZSMBnNjYWxhcpSTlIwFbnVtcHmUjAVkdHlwZZSTlIwCZjiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYkMIBOYhUz6PcUCUhpRSlIwBbJRLuowBdJRHQK1ZT2TxG2F1fZQoaAZoCWgPQwjOiT20jw5vQJSGlFKUaBVLl2gWR0CtWXPRzBAOdX2UKGgGaAloD0MI/RadLPU6cECUhpRSlGgVS59oFkdArVmSNIbwSnV9lChoBmgJaA9DCPBMaJIY8nFAlIaUUpRoFUuwaBZHQK1Zo+AVfu11fZQoaAZoCWgPQwhOCvMe5ylzQJSGlFKUaBVL0WgWR0CtWa/i5uqFdX2UKGgGaAloD0MIUYL+Qk8TcUCUhpRSlGgVS6loFkdArVoE0Nz8xnV9lChoBmgJaA9DCLfUQV6P8HFAlIaUUpRoFUuLaBZHQK1aOl8gIQh1fZQoaAZoCWgPQwhLXMe4IiNzQJSGlFKUaBVLsWgWR0CtWkvkq+ajdX2UKGgGaAloD0MI09o0tpeMcECUhpRSlGgVS61oFkdArVpTxgAp8XV9lChoBmgJaA9DCIL/rWSHK3JAlIaUUpRoFUuyaBZHQK1aZkhA4XJ1fZQoaAZoCWgPQwjDSC9qN0lzQJSGlFKUaBVLu2gWR0CtWnPKlpGndX2UKGgGaAloD0MIUWnEzH6EdECUhpRSlGgVS+loFkdArVqEySFGonV9lChoBmgJaA9DCCx96II6B3FAlIaUUpRoFUuJaBZHQK1aiJ79hql1fZQoaAZoCWgPQwj68ZcW9fxwQJSGlFKUaBVLlmgWR0CtWrdhZyMldX2UKGgGaAloD0MIEHS0qiWqcUCUhpRSlGgVS7VoFkdArVrEs6JZXHV9lChoBmgJaA9DCIjyBS2kD3FAlIaUUpRoFUuGaBZHQK1a2TEBKcx1fZQoaAZoCWgPQwjjbaXXprhyQJSGlFKUaBVLvmgWR0CtWuPR7Z3+dX2UKGgGaAloD0MIntMs0G4Lc0CUhpRSlGgVS6RoFkdArWSsx20Re3V9lChoBmgJaA9DCF+zXDZ603JAlIaUUpRoFUvGaBZHQK1kxLM9r451fZQoaAZoCWgPQwgqb0c4bQxzQJSGlFKUaBVLtmgWR0CtZM76P8yfdX2UKGgGaAloD0MIjKGcaBctckCUhpRSlGgVS6toFkdArWUbyrgfl3V9lChoBmgJaA9DCKK2DaPgG3JAlIaUUpRoFUuaaBZHQK1lPocJdB11fZQoaAZoCWgPQwhHOgMj7zVwQJSGlFKUaBVLlGgWR0CtZVAB1cMWdX2UKGgGaAloD0MIHTo978YEb0CUhpRSlGgVS5FoFkdArWVdymygPHV9lChoBmgJaA9DCNL9nII8jXJAlIaUUpRoFUusaBZHQK1lZL0z0pV1fZQoaAZoCWgPQwgzVMVU+txwQJSGlFKUaBVLsWgWR0CtZYqe9SMtdX2UKGgGaAloD0MIesISDyhacUCUhpRSlGgVS5BoFkdArWWue8PFvXV9lChoBmgJaA9DCCoDB7R07HFAlIaUUpRoFUu3aBZHQK1lt/IbOu91fZQoaAZoCWgPQwgWF0flZohzQJSGlFKUaBVL4GgWR0CtZdPX9R77dX2UKGgGaAloD0MIZLK4/0hVckCUhpRSlGgVS7hoFkdArWXu63AmA3V9lChoBmgJaA9DCHTS+8bXy3JAlIaUUpRoFUu9aBZHQK1mBUfgaWJ1fZQoaAZoCWgPQwiWICOgQkVyQJSGlFKUaBVLkmgWR0CtZi36ZYxMdX2UKGgGaAloD0MIT135LI+ncUCUhpRSlGgVS5xoFkdArWYwx8D0UXV9lChoBmgJaA9DCBrAWyDBenJAlIaUUpRoFUuZaBZHQK1mR8LKFIx1fZQoaAZoCWgPQwgXRnpRu8BwQJSGlFKUaBVLmGgWR0CtZrMbedkKdX2UKGgGaAloD0MI0sQ7wJPqc0CUhpRSlGgVS7BoFkdArWbPRmbsnnV9lChoBmgJaA9DCBR15h4SlElAlIaUUpRoFUt5aBZHQK1m2kY4yXV1fZQoaAZoCWgPQwixxAPKJlhwQJSGlFKUaBVLqWgWR0CtZwqcd5prdX2UKGgGaAloD0MIlBRYANMkckCUhpRSlGgVS8JoFkdArWc3N7jT8nV9lChoBmgJaA9DCLRZ9bnaXHJAlIaUUpRoFUutaBZHQK1nPZ3cHnl1fZQoaAZoCWgPQwgoDMo0GmxyQJSGlFKUaBVLzWgWR0CtZ2HfEXLvdX2UKGgGaAloD0MI2AsFbIcMcUCUhpRSlGgVS6NoFkdArWdwQz1scnV9lChoBmgJaA9DCDVeuklMJ3FAlIaUUpRoFUuIaBZHQK1nib6xgRd1fZQoaAZoCWgPQwg5JSAmIRR0QJSGlFKUaBVLs2gWR0CtZ7JyyUs4dX2UKGgGaAloD0MI7zmwHGE5ckCUhpRSlGgVS8toFkdArWe2lCTlk3V9lChoBmgJaA9DCMQGCyepbHJAlIaUUpRoFUuuaBZHQK1nvgAp8Wt1fZQoaAZoCWgPQwifjzLigvRwQJSGlFKUaBVLrmgWR0CtZ+gmzBykdX2UKGgGaAloD0MIz9cslw1qc0CUhpRSlGgVS71oFkdArWgiV+qioXV9lChoBmgJaA9DCPDce7gkLnBAlIaUUpRoFUuUaBZHQK1oSnQY1pF1fZQoaAZoCWgPQwgCnN7FuyJzQJSGlFKUaBVLr2gWR0CtaIdhAnlXdX2UKGgGaAloD0MIuY0G8BaEb0CUhpRSlGgVS5VoFkdArWivNke6qnV9lChoBmgJaA9DCAcJUb7gjnFAlIaUUpRoFUvOaBZHQK1ovfAKv3d1fZQoaAZoCWgPQwje5SK+08VwQJSGlFKUaBVLsGgWR0CtaMN8NQTFdX2UKGgGaAloD0MIjZqvkk8ac0CUhpRSlGgVS7doFkdArWkDWsijcnV9lChoBmgJaA9DCHZrmQxHXHJAlIaUUpRoFUuXaBZHQK1pBpJwsGx1fZQoaAZoCWgPQwguNxjqMIVxQJSGlFKUaBVLs2gWR0CtaTJ7TlT4dX2UKGgGaAloD0MIS6yMRn6ScUCUhpRSlGgVS81oFkdArWllyimEXnV9lChoBmgJaA9DCBdFD3zM2XFAlIaUUpRoFUuzaBZHQK1pfKaG5+Z1fZQoaAZoCWgPQwjZ0M3+gFpyQJSGlFKUaBVLuWgWR0CtaYfVI7NjdX2UKGgGaAloD0MIOzYC8ToRckCUhpRSlGgVS7VoFkdArWmJbhWHUXV9lChoBmgJaA9DCIOJP4o6j3BAlIaUUpRoFUuVaBZHQK1po1LrX191fZQoaAZoCWgPQwh3ZKw2P/pxQJSGlFKUaBVLr2gWR0CtaaYNAkcCdX2UKGgGaAloD0MIPPTdraxKcUCUhpRSlGgVS4hoFkdArWnhrcj7h3V9lChoBmgJaA9DCApJZvWOrG9AlIaUUpRoFUueaBZHQK1qP9kz41x1fZQoaAZoCWgPQwhKmj+mtVRyQJSGlFKUaBVLxWgWR0CtakJZfUnYdX2UKGgGaAloD0MI+69z02YhcUCUhpRSlGgVS69oFkdArWp9d5Y5k3V9lChoBmgJaA9DCBIT1PAtmW9AlIaUUpRoFUuWaBZHQK1qgzIFNcp1fZQoaAZoCWgPQwhPkNjunq9vQJSGlFKUaBVLr2gWR0CtaoOhkAggdX2UKGgGaAloD0MIz6EMVTHzcECUhpRSlGgVS6JoFkdArWqhAGB4EHV9lChoBmgJaA9DCOFh2jc3unJAlIaUUpRoFUuVaBZHQK1q4RFqi491fZQoaAZoCWgPQwg2XOSerotxQJSGlFKUaBVLoWgWR0Ctay2BJ7LMdX2UKGgGaAloD0MIUz4EVSNBcECUhpRSlGgVS8ZoFkdArWs3L3bmEHV9lChoBmgJaA9DCPUUOUTcdHFAlIaUUpRoFUusaBZHQK1rPqs2ehB1fZQoaAZoCWgPQwj/JD53gsZzQJSGlFKUaBVLqmgWR0Cta2bFCLMtdX2UKGgGaAloD0MIj4tqEVF3c0CUhpRSlGgVS7poFkdArWtyews5GXV9lChoBmgJaA9DCERrRZvjUnJAlIaUUpRoFUuwaBZHQK1rvHc1wYN1fZQoaAZoCWgPQwjxngPLkQNkQJSGlFKUaBVN6ANoFkdArWwCA6Mir3V9lChoBmgJaA9DCPdZZaY0XHNAlIaUUpRoFUupaBZHQK1sEEf1Yhd1fZQoaAZoCWgPQwjGNNO9zstwQJSGlFKUaBVLhmgWR0CtbBAPd2xIdX2UKGgGaAloD0MIPpRoyeOWcECUhpRSlGgVS7hoFkdArWwz1schknV9lChoBmgJaA9DCIDwoUQLiHBAlIaUUpRoFUulaBZHQK1sQVcD8tR1fZQoaAZoCWgPQwjhlo+kpCpyQJSGlFKUaBVLt2gWR0CtbGyH/LkkdX2UKGgGaAloD0MI5XtGIvSMcUCUhpRSlGgVS71oFkdArWx2SB9TgnV9lChoBmgJaA9DCHu7JTlgZXNAlIaUUpRoFUu5aBZHQK1sy/N7jT91fZQoaAZoCWgPQwh7+Z0m87pxQJSGlFKUaBVLmmgWR0CtbM2/BWPtdX2UKGgGaAloD0MIWWlSCjp6cECUhpRSlGgVS6ZoFkdArWzcxqO94HV9lChoBmgJaA9DCFGC/kJPAHFAlIaUUpRoFUujaBZHQK1tFKYAsCl1fZQoaAZoCWgPQwhOe0rOSQ5wQJSGlFKUaBVLkWgWR0CtbSutwJgLdX2UKGgGaAloD0MIx9Rd2cWdckCUhpRSlGgVS85oFkdArW1JO+IuXnV9lChoBmgJaA9DCJLLf0g/EXFAlIaUUpRoFUu+aBZHQK1tS3QUpNN1fZQoaAZoCWgPQwhM4qyImjhyQJSGlFKUaBVLmGgWR0CtbXenyd4FdX2UKGgGaAloD0MIK8O4G0TtcUCUhpRSlGgVS4hoFkdArW2OTot+TnV9lChoBmgJaA9DCL7Z5sb0hG9AlIaUUpRoFUucaBZHQK1tjnOjZct1fZQoaAZoCWgPQwihZ7PqsydxQJSGlFKUaBVLqGgWR0Ctbc3w9aEBdX2UKGgGaAloD0MI38FPHAB0ckCUhpRSlGgVS8poFkdArW4BIBikPHV9lChoBmgJaA9DCOnSvyQVPmZAlIaUUpRoFU3oA2gWR0CtbkKWcBludX2UKGgGaAloD0MIkq8EUuKPckCUhpRSlGgVS7xoFkdArW5OkcjqwHV9lChoBmgJaA9DCBzPZ0B9oHJAlIaUUpRoFUvNaBZHQK1ucCzTnaF1fZQoaAZoCWgPQwgwgPChRJtxQJSGlFKUaBVLv2gWR0CtbsBbW3BpdX2UKGgGaAloD0MIfLQ4Y5ijc0CUhpRSlGgVS8loFkdArW7JUxVQynVlLg=="}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 2448, "n_steps": 1024, "gamma": 0.99, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 128, "n_epochs": 8, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.15", "Stable-Baselines3": "1.6.2", "PyTorch": "1.12.1+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}
+{"policy_class": {":type:": "<class 'abc.ABCMeta'>", ":serialized:": "gAWVOwAAAAAAAACMIXN0YWJsZV9iYXNlbGluZXMzLmNvbW1vbi5wb2xpY2llc5SMEUFjdG9yQ3JpdGljUG9saWN5lJOULg==", "__module__": "stable_baselines3.common.policies", "__doc__": "\n    Policy class for actor-critic algorithms (has both policy and value prediction).\n    Used by A2C, PPO and the likes.\n\n    :param observation_space: Observation space\n    :param action_space: Action space\n    :param lr_schedule: Learning rate schedule (could be constant)\n    :param net_arch: The specification of the policy and value networks.\n    :param activation_fn: Activation function\n    :param ortho_init: Whether to use or not orthogonal initialization\n    :param use_sde: Whether to use State Dependent Exploration or not\n    :param log_std_init: Initial value for the log standard deviation\n    :param full_std: Whether to use (n_features x n_actions) parameters\n        for the std instead of only (n_features,) when using gSDE\n    :param sde_net_arch: Network architecture for extracting features\n        when using gSDE. If None, the latent features from the policy will be used.\n        Pass an empty list to use the states as features.\n    :param use_expln: Use ``expln()`` function instead of ``exp()`` to ensure\n        a positive standard deviation (cf paper). It allows to keep variance\n        above zero and prevent it from growing too fast. In practice, ``exp()`` is usually enough.\n    :param squash_output: Whether to squash the output using a tanh function,\n        this allows to ensure boundaries when using gSDE.\n    :param features_extractor_class: Features extractor to use.\n    :param features_extractor_kwargs: Keyword arguments\n        to pass to the features extractor.\n    :param normalize_images: Whether to normalize images or not,\n         dividing by 255.0 (True by default)\n    :param optimizer_class: The optimizer to use,\n        ``th.optim.Adam`` by default\n    :param optimizer_kwargs: Additional keyword arguments,\n        excluding the learning rate, to pass to the optimizer\n    ", "__init__": "<function ActorCriticPolicy.__init__ at 0x7f180eda8c10>", "_get_constructor_parameters": "<function ActorCriticPolicy._get_constructor_parameters at 0x7f180eda8ca0>", "reset_noise": "<function ActorCriticPolicy.reset_noise at 0x7f180eda8d30>", "_build_mlp_extractor": "<function ActorCriticPolicy._build_mlp_extractor at 0x7f180eda8dc0>", "_build": "<function ActorCriticPolicy._build at 0x7f180eda8e50>", "forward": "<function ActorCriticPolicy.forward at 0x7f180eda8ee0>", "_get_action_dist_from_latent": "<function ActorCriticPolicy._get_action_dist_from_latent at 0x7f180eda8f70>", "_predict": "<function ActorCriticPolicy._predict at 0x7f180edac040>", "evaluate_actions": "<function ActorCriticPolicy.evaluate_actions at 0x7f180edac0d0>", "get_distribution": "<function ActorCriticPolicy.get_distribution at 0x7f180edac160>", "predict_values": "<function ActorCriticPolicy.predict_values at 0x7f180edac1f0>", "__abstractmethods__": "frozenset()", "_abc_impl": "<_abc_data object at 0x7f180eda58a0>"}, "verbose": 1, "policy_kwargs": {}, "observation_space": {":type:": "<class 'gym.spaces.box.Box'>", ":serialized:": "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", "dtype": "float32", "_shape": [8], "low": "[-inf -inf -inf -inf -inf -inf -inf -inf]", "high": "[inf inf inf inf inf inf inf inf]", "bounded_below": "[False False False False False False False False]", "bounded_above": "[False False False False False False False False]", "_np_random": null}, "action_space": {":type:": "<class 'gym.spaces.discrete.Discrete'>", ":serialized:": "gAWVggAAAAAAAACME2d5bS5zcGFjZXMuZGlzY3JldGWUjAhEaXNjcmV0ZZSTlCmBlH2UKIwBbpRLBIwGX3NoYXBllCmMBWR0eXBllIwFbnVtcHmUaAeTlIwCaTiUiYiHlFKUKEsDjAE8lE5OTkr/////Sv////9LAHSUYowKX25wX3JhbmRvbZROdWIu", "n": 4, "_shape": [], "dtype": "int64", "_np_random": null}, "n_envs": 16, "num_timesteps": 2506752, "_total_timesteps": 2500000, "_num_timesteps_at_start": 0, "seed": null, "action_noise": null, "start_time": 1670392316716156993, "learning_rate": 0.0003, "tensorboard_log": null, "lr_schedule": {":type:": "<class 'function'>", ":serialized:": "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"}, "_last_obs": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "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"}, "_last_episode_starts": {":type:": "<class 'numpy.ndarray'>", ":serialized:": "gAWVgwAAAAAAAACMEm51bXB5LmNvcmUubnVtZXJpY5SMC19mcm9tYnVmZmVylJOUKJYQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACUjAVudW1weZSMBWR0eXBllJOUjAJiMZSJiIeUUpQoSwOMAXyUTk5OSv////9K/////0sAdJRiSxCFlIwBQ5R0lFKULg=="}, "_last_original_obs": null, "_episode_num": 0, "use_sde": false, "sde_sample_freq": -1, "_current_progress_remaining": -0.0027007999999999477, "ep_info_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "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"}, "ep_success_buffer": {":type:": "<class 'collections.deque'>", ":serialized:": "gAWVIAAAAAAAAACMC2NvbGxlY3Rpb25zlIwFZGVxdWWUk5QpS2SGlFKULg=="}, "_n_updates": 3672, "n_steps": 1024, "gamma": 0.99, "gae_lambda": 0.98, "ent_coef": 0.01, "vf_coef": 0.5, "max_grad_norm": 0.5, "batch_size": 128, "n_epochs": 8, "clip_range": {":type:": "<class 'function'>", ":serialized:": "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"}, "clip_range_vf": null, "normalize_advantage": true, "target_kl": null, "system_info": {"OS": "Linux-5.10.133+-x86_64-with-glibc2.27 #1 SMP Fri Aug 26 08:44:51 UTC 2022", "Python": "3.8.15", "Stable-Baselines3": "1.6.2", "PyTorch": "1.12.1+cu113", "GPU Enabled": "True", "Numpy": "1.21.6", "Gym": "0.21.0"}}

results.json

@@ -1 +1 @@
-{"mean_reward": 284.8546140067962, "std_reward": 21.901643164492715, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-07T05:51:35.297553"}
+{"mean_reward": 289.38317778628704, "std_reward": 20.951980540227904, "is_deterministic": true, "n_eval_episodes": 10, "eval_datetime": "2022-12-07T06:16:55.822214"}