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https://github.com/mryellow/maze_explorer
A simple maze exploration game for AI agents
https://github.com/mryellow/maze_explorer
game maze maze-explorer openai-gym openai-gym-environments
Last synced: 2 months ago
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A simple maze exploration game for AI agents
- Host: GitHub
- URL: https://github.com/mryellow/maze_explorer
- Owner: mryellow
- License: mit
- Created: 2017-07-21T01:25:31.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2019-09-29T00:21:39.000Z (over 5 years ago)
- Last Synced: 2024-04-29T23:48:13.475Z (9 months ago)
- Topics: game, maze, maze-explorer, openai-gym, openai-gym-environments
- Language: Python
- Homepage:
- Size: 436 KB
- Stars: 6
- Watchers: 3
- Forks: 4
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Maze Explorer
A maze exploration game for AI agents.
## TODO:
* [ ] New game modes
* [ ] Terminal state for human, with switch for god-mode
* [ ] Zoomed scrolling view for human players
## Installation
### Source
```bash
git clone https://github.com/mryellow/maze_explorer.git
cd maze_explorer
pip install -e .
```
### Package
```bash
pip install mazeexp
```
## Standalone
`python standalone.py`
### Options
```bash
--mode X # Mode number
--random # Execute random actions step-by-step via `act`
--step # Call the engine step-by-step via `step`
```
## OpenAIGym
[gym-mazeexplorer](https://github.com/mryellow/gym-mazeexplorer)
### Game modes
#### Mode 0 `MazeExplorerEat-v0`
Apples and poison.
Based on [Andrej Karpathy's Javascript environment](https://cs.stanford.edu/people/karpathy/convnetjs/demo/rldemo.html)
##### State
```
[
[min(wall_range, apple_range, poison_range), apple_range, poison_range],
...
]
```
##### Rewards
* ~~`avg(proximity) or 1` Agents don't like seeing walls, especially up close~~
* ~~`*1.1` Forward action bonus~~
* `-10` collision with wall
* `+5` collision with apple
* `-6` collision with poison
##### Terminal
* None
#### Mode 1 `MazeExplorerExplore-v0`
Explore the maze and make it back to spawn before battery runs out.
##### State
```
[wall_range, ..., battery]
```
##### Rewards
* `-100` collision with wall
* `-100` battery out
###### When battery above 50%
* `+1` exploration reward on first visit to tile and for each of it's open neighbours
The `visited` state is not observable in environment and reward is generated by ground-truth.
Thus agent must keep it's own internal state and/or develop a policy which overcomes this unknown.
###### When battery below 50%
* `+200` reward goal state on reaching spawn tile
* No futher exploration rewards
Spawn tile is no different to any other from agents perspective, must remember how to return to it or develop a policy which increases the likelihood of such.
##### Terminal
* Wall collision
* Battery out
* Return to home goal
## Cite
If you use Maze Explorer in your academic research, we would be grateful if you could cite it as follows:
```
@misc{mryellow2017mazeexplorer,
author = {Mr-Yellow},
title = {Maze Explorer: A maze exploration game for AI agents},
howpublished={Web page},
url = {https://github.com/mryellow/maze_explorer},
year = {2017}
}
```