File size: 2,214 Bytes
35a79ac
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
---
library_name: stable-baselines3
tags:
- MountainCarContinuous-v0
- deep-reinforcement-learning
- reinforcement-learning
- stable-baselines3
model-index:
- name: DDPG
  results:
  - task:
      type: reinforcement-learning
      name: reinforcement-learning
    dataset:
      name: MountainCarContinuous-v0
      type: MountainCarContinuous-v0
    metrics:
    - type: mean_reward
      value: 93.72 +/- 0.13
      name: mean_reward
      verified: false
---

# **DDPG** Agent playing **MountainCarContinuous-v0**
This is a trained model of a **DDPG** agent playing **MountainCarContinuous-v0**
using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3)
and the [RL Zoo](https://github.com/DLR-RM/rl-baselines3-zoo).

The RL Zoo is a training framework for Stable Baselines3
reinforcement learning agents,
with hyperparameter optimization and pre-trained agents included.

## Usage (with SB3 RL Zoo)

RL Zoo: https://github.com/DLR-RM/rl-baselines3-zoo<br/>
SB3: https://github.com/DLR-RM/stable-baselines3<br/>
SB3 Contrib: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib

Install the RL Zoo (with SB3 and SB3-Contrib):
```bash
pip install rl_zoo3
```

```
# Download model and save it into the logs/ folder
python -m rl_zoo3.load_from_hub --algo ddpg --env MountainCarContinuous-v0 -orga qgallouedec -f logs/
python -m rl_zoo3.enjoy --algo ddpg --env MountainCarContinuous-v0  -f logs/
```

If you installed the RL Zoo3 via pip (`pip install rl_zoo3`), from anywhere you can do:
```
python -m rl_zoo3.load_from_hub --algo ddpg --env MountainCarContinuous-v0 -orga qgallouedec -f logs/
python -m rl_zoo3.enjoy --algo ddpg --env MountainCarContinuous-v0  -f logs/
```

## Training (with the RL Zoo)
```
python -m rl_zoo3.train --algo ddpg --env MountainCarContinuous-v0 -f logs/
# Upload the model and generate video (when possible)
python -m rl_zoo3.push_to_hub --algo ddpg --env MountainCarContinuous-v0 -f logs/ -orga qgallouedec
```

## Hyperparameters
```python
OrderedDict([('n_timesteps', 300000),
             ('noise_std', 0.5),
             ('noise_type', 'ornstein-uhlenbeck'),
             ('policy', 'MlpPolicy'),
             ('normalize', False)])
```