tile-match-gym
Tile matching gym environment for reinforcement learning research.
Science Score: 44.0%
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✓CITATION.cff file
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✓codemeta.json file
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✓.zenodo.json file
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○DOI references
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○Academic publication links
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○Committers with academic emails
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (8.0%) to scientific vocabulary
Keywords
Repository
Tile matching gym environment for reinforcement learning research.
Basic Info
Statistics
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 3
- Releases: 0
Topics
Metadata Files
README.md
Tile Matching Reinforcement Learning Environments
Welcome to the Reinforcement Learning Environments for Tile Matching Games repository! Here you can find a collection of tile matching game environments (like Bejeweled or Candy Crush), poised to push reinforcement learning research forwards.
This genre of games is characterised by the following features, which we find useful for reinforcement learning research:
- Large action spaces
- Intuitive action hierarchies
- Procedurally generated levels
- Structured complex stochasticity in transition dynamics
Installation
You can install the package via pip:
pip install tile-match-gym
Example Usage
We follow the the Farama Foundation Gymnasium API:
``` from tilematchgym.tilematchenv import TileMatchEnv
env = TileMatchEnv( numrows=10, numcols=10, numcolours=4, nummoves=30, colourlessspecials=["cookie"], colourspecials=["verticallaser", "horizontallaser", "bomb"], seed=2 render_mode="human", )
obs, _ = env.reset()
while True: action = env.actionspace.sample() nextobs, reward, done, truncated, info = env.step(action) env.render() if done: break else: obs = next_obs ```
Citation
We'd love it if you use our package for your research! If you do use code from this repository please cite us as below:
@software{tile_match_gym,
author = {Patel, Akshil and Elson, James},
title = {{Tile Matching Game Reinforcement Learning Environments}},
url = {https://github.com/akshilpatel/tile-match-gym},
version = {1.0.6},
year = {2023}
}
Owner
- Name: Akshil Patel
- Login: akshilpatel
- Kind: user
- Repositories: 1
- Profile: https://github.com/akshilpatel
PhD candidate at University of Bath working on Intrinsically Motivated and Hierarchical Reinforcement Learning.
Citation (CITATION.bib)
@software{tile_match_gym,
author = {Patel, Akshil and Elson, James},
title = {{Tile Matching Reinforcement Learning Environments}},
url = {https://github.com/akshilpatel/tile-match-gym},
version = {1.0.6},
year = {2023}
}
GitHub Events
Total
- Issues event: 2
- Watch event: 1
- Delete event: 2
- Issue comment event: 1
- Push event: 11
- Pull request event: 2
- Create event: 1
Last Year
- Issues event: 2
- Watch event: 1
- Delete event: 2
- Issue comment event: 1
- Push event: 11
- Pull request event: 2
- Create event: 1
Committers
Last synced: 9 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| akshilpatel | a****1@g****m | 215 |
| James Elson | j****9@g****m | 57 |
Issues and Pull Requests
Last synced: 9 months ago
All Time
- Total issues: 10
- Total pull requests: 3
- Average time to close issues: 5 months
- Average time to close pull requests: less than a minute
- Total issue authors: 1
- Total pull request authors: 1
- Average comments per issue: 0.4
- Average comments per pull request: 0.33
- Merged pull requests: 3
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 1
- Pull requests: 2
- Average time to close issues: about 1 hour
- Average time to close pull requests: less than a minute
- Issue authors: 1
- Pull request authors: 1
- Average comments per issue: 0.0
- Average comments per pull request: 0.5
- Merged pull requests: 2
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- akshilpatel (10)
Pull Request Authors
- akshilpatel (6)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- pypi 81 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 12
- Total maintainers: 1
pypi.org: tile-match-gym
A set of reinforcement learning environments for tile matching games, consistent with the OpenAI Gymnasium API.
- Homepage: https://github.com/akshilpatel/tile-match-gym
- Documentation: https://tile-match-gym.readthedocs.io/
- License: Copyright (c) 2023, Akshil Patel Copyright (c) 2023, James Elson All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the name of tile-match-gym nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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Latest release: 1.0.6
published over 1 year ago