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https://github.com/zsdonghao/Imitation-Learning-Dagger-Torcs
A Simple Example for Imitation Learning with Dataset Aggregation (DAGGER) on Torcs Env
https://github.com/zsdonghao/Imitation-Learning-Dagger-Torcs
dagger gym-torcs imitation-learning tensorflow tensorflow-tutorials tensorlayer torcs torcs-env
Last synced: about 1 month ago
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A Simple Example for Imitation Learning with Dataset Aggregation (DAGGER) on Torcs Env
- Host: GitHub
- URL: https://github.com/zsdonghao/Imitation-Learning-Dagger-Torcs
- Owner: zsdonghao
- Created: 2017-08-10T17:33:43.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2017-08-10T19:42:20.000Z (over 7 years ago)
- Last Synced: 2024-10-11T08:41:41.507Z (2 months ago)
- Topics: dagger, gym-torcs, imitation-learning, tensorflow, tensorflow-tutorials, tensorlayer, torcs, torcs-env
- Language: Python
- Homepage: https://github.com/zsdonghao/tensorlayer
- Size: 13.7 KB
- Stars: 71
- Watchers: 4
- Forks: 28
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-tensorflow - DAGGER - For Playing [Gym Torcs](https://github.com/ugo-nama-kun/gym_torcs) (Models/Projects)
- awesome-tensorflow - DAGGER - For Playing [Gym Torcs](https://github.com/ugo-nama-kun/gym_torcs) (Models/Projects)
- fucking-awesome-tensorflow - DAGGER - For Playing <b><code> 407⭐</code></b> <b><code> 163🍴</code></b> [Gym Torcs](https://github.com/ugo-nama-kun/gym_torcs)) (Models/Projects)
README
## Imitation Learning with Dataset Aggregation (DAGGER) on Torcs Env
This repository implements a simple algorithm for imitation learning: [DAGGER](https://www.cs.cmu.edu/~sross1/publications/Ross-AIStats11-NoRegret.pdf).
In this example, the agent only learns to control the steer [-1, 1], the speed is computed
automatically in `gym_torcs.TorcsEnv`.## Requirements
1. Ubuntu (I only test on this)
2. Python 3
3. TensorLayer and TensorFlow
4. [Gym-Torcs](https://github.com/ugo-nama-kun/gym_torcs)## Setting Up
It is a little bit boring to set up the environment, but any incorrect configurations will lead to FAILURE.
After installing [Gym-Torcs](https://github.com/ugo-nama-kun/gym_torcs), please follow the instructions to confirm everything work well:- Open a terminal:
- Run `sudo torcs -vision` to start a game
- `Race --> Practice --> Configure Race`: set the driver to `scr_server 1` instead of `player`
- Open Torcs server by selecting `Race --> Practice --> New Race`:
This should result that Torcs keeps a blue screen with several text information.- Open another terminal:
- Run `python snakeoil3_gym.py` on another terminal, it will shows how the fake AI control the car.
- Press F2 to see the driver view.- Set image size to 64x64x3:
- The model is trained on 64x64 RGB observation.
- Run `sudo torcs -vision` to start a game
- `Options --> Display --> select 64x64 --> Apply`## Usage
Make sure everything above work well and then run:- `python dagger.py`
It will start a Torcs server at the beginning of every episode, and terminate the server when the car crashs or the speed is too low.
Note that, the self-contained `gym_torcs.py` is modified from [Gym-Torcs](https://github.com/ugo-nama-kun/gym_torcs), you can try different settings (like default speed, terminated speed) by modifying it.## Results
After Episode 1, the car crashes after 315 steps.
![](http://i.imgur.com/YfqFXQZ.gif)
After Episode 3, the car does not crash anymore !!!
![](http://i.imgur.com/doz8U0z.gif)
The number of steps and episodes might vary depending on the parameters initialization.
ENJOY !