|
--- |
|
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: 8.40 +/- 2.54 |
|
name: mean_reward |
|
verified: false |
|
--- |
|
|
|
# **Q-Learning** Agent playing1 **FrozenLake-v1** |
|
This is a trained model of a **Q-Learning** agent playing **Taxi-v3** . |
|
|
|
## Usage |
|
|
|
```python |
|
|
|
model = load_from_hub(repo_id="peteozegov/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"]) |
|
``` |
|
|
