| tags: | |
| - reinforcement-learning | |
| - Taxi-v3 | |
| - q-learning | |
| - deep-rl-course | |
| 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: 7.69 +/- 2.87 | |
| name: mean_reward | |
| # Q-Learning Agent playing Taxi-v3 | |
| This is a trained model of a **Tabular Q-Learning agent** playing `Taxi-v3`. | |
| The agent was trained and evaluated directly using the Bellman optimality update equation. | |
| ### Evaluation Results | |
| - **Mean Reward**: `7.69 +/- 2.87` (Passing threshold: $\ge 4.0$) | |
| - **Number of Evaluation Episodes**: 100 | |
| - **Model weights**: Saved in `q_table.pkl` | |
| Trained and submitted by **Subhash3008**. | |