Upload folder using huggingface_hub
Browse files- README.md +35 -0
- q-learning.pkl +3 -0
- replay.mp4 +0 -0
- results.json +1 -0
README.md
ADDED
@@ -0,0 +1,35 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
tags:
|
3 |
+
- Taxi-v3
|
4 |
+
- q-learning
|
5 |
+
- reinforcement-learning
|
6 |
+
- custom-implementation
|
7 |
+
model-index:
|
8 |
+
- name: Taxi
|
9 |
+
results:
|
10 |
+
- task:
|
11 |
+
type: reinforcement-learning
|
12 |
+
name: reinforcement-learning
|
13 |
+
dataset:
|
14 |
+
name: Taxi-v3
|
15 |
+
type: Taxi-v3
|
16 |
+
metrics:
|
17 |
+
- type: mean_reward
|
18 |
+
value: 7.54 +/- 2.73
|
19 |
+
name: mean_reward
|
20 |
+
verified: false
|
21 |
+
---
|
22 |
+
|
23 |
+
# **Q-Learning** Agent playing1 **Taxi-v3**
|
24 |
+
This is a trained model of a **Q-Learning** agent playing **Taxi-v3** .
|
25 |
+
|
26 |
+
## Usage
|
27 |
+
|
28 |
+
```python
|
29 |
+
|
30 |
+
model = load_from_hub(repo_id="EthanQ/Taxi", filename="q-learning.pkl")
|
31 |
+
|
32 |
+
# Don't forget to check if you need to add additional attributes (is_slippery=False etc)
|
33 |
+
env = gym.make(model["env_id"])
|
34 |
+
```
|
35 |
+
|
q-learning.pkl
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:3a0091f6526652e088ae9c9951e1f73bca704e5781ff5e0ccf50366e05381dff
|
3 |
+
size 24570
|
replay.mp4
ADDED
Binary file (116 kB). View file
|
|
results.json
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"env_id": "Taxi-v3", "mean_reward": 7.54, "n_eval_episodes": 100, "eval_datetime": "2023-12-05T13:18:47.543858"}
|