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README.md

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+---
+tags:
+- Taxi-v3
+- q-learning
+- reinforcement-learning
+- custom-implementation
+model-index:
+- name: Q-Taxi-V3
+  results:
+  - task:
+      type: reinforcement-learning
+      name: reinforcement-learning
+    dataset:
+      name: Taxi-v3
+      type: Taxi-v3
+    metrics:
+    - type: mean_reward
+      value: 7.56 +/- 2.71
+      name: mean_reward
+      verified: false
+---
+
+  # **Q-Learning** Agent playing1 **Taxi-v3**
+  This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
+
+  ## Usage
+
+  ```python
+
+  model = load_from_hub(repo_id="Arikkod/Q-Taxi-V3", filename="q-learning.pkl")
+
+  # Don't forget to check if you need to add additional attributes (is_slippery=False etc)
+  env = gym.make(model["env_id"])
+  ```
+  

q-learning.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:67e952e0230abdae429650f6ae281d825ef078f55bb09eea1115a0d64ef30a90
+oid sha256:1051094c53bc1e411025135cfdf05539ac4b3e9a539eba2d4c97b178a2d48060
 size 24572

results.json

@@ -1 +1 @@
-{"env_id": "Taxi-v3", "mean_reward": 7.56, "n_eval_episodes": 100, "eval_datetime": "2023-07-22T16:52:20.425323"}
+{"env_id": "Taxi-v3", "mean_reward": 7.56, "n_eval_episodes": 100, "eval_datetime": "2023-07-22T16:54:30.120098"}