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README.md

@@ -1,6 +1,6 @@
 ---
 tags:
-- Taxi-v3
+- FrozenLake-v1-4x4
 - q-learning
 - reinforcement-learning
 - custom-implementation
@@ -11,17 +11,17 @@ model-index:
       type: reinforcement-learning
       name: reinforcement-learning
     dataset:
-      name: Taxi-v3
-      type: Taxi-v3
+      name: FrozenLake-v1-4x4
+      type: FrozenLake-v1-4x4
     metrics:
     - type: mean_reward
-      value: 7.56 +/- 2.71
+      value: 0.75 +/- 0.43
       name: mean_reward
       verified: false
 ---
  
-# **Q-Learning** Agent playing1 **Taxi-v3** 
-This is a trained model of a **Q-Learning** agent playing **Taxi-v3** . 
+# **Q-Learning** Agent playing1 **FrozenLake-v1** 
+This is a trained model of a **Q-Learning** agent playing **FrozenLake-v1** . 
 ## Usage 
 ```python 
 model = load_from_hub(repo_id="YCHuang2112/q-FrozenLake-v1-4x4-Slippery", filename="q-learning.pkl") 

q-learning.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:db7eb65b0a874cb69f4c0d3448a2f02d796b7b99c69df88cf225c744d6ae000d
-size 24571
+oid sha256:5d63a7269dbadbaa863e91b5c02e43f545fda5bc37d1d3e9d303f92bb9b428e4
+size 897

results.json

@@ -1 +1 @@
-{"env_id": "Taxi-v3", "mean_reward": 7.56, "n_eval_episodes": 100, "eval_datetime": "2023-05-28T11:11:45.274327"}
+{"env_id": "FrozenLake-v1", "mean_reward": 0.75, "n_eval_episodes": 100, "eval_datetime": "2023-05-28T11:28:30.303134"}