ma-gym
rlcard
| ma-gym | rlcard | |
|---|---|---|
| 2 | 5 | |
| 522 | 2,709 | |
| - | 2.3% | |
| 6.1 | 6.2 | |
| 3 months ago | 3 months ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ma-gym
-
Tensorflow and OpenAI Gym for Multi-Agent Reinforcement Learning?
Of course I conducted research (or rather... searched on google :)) before making this post. I found a simple third party gym environment that implements multi-agent rl called 'ma-gym' (https://github.com/koulanurag/ma-gym) but I'm not quite sure how I would train two Agents and let them play inside one environment.
-
How do you train Agent for something like Chess or Game of the Generals?
There are projects working on a multi agent version of gym. Maybe you find some inspiration there.
rlcard
- [P] Looking for RL or rules-based No-Limit Hold 'Em Work
-
Self play environments
Hi. I’ve decided to do a project to adapt an rl library to support self-play. This is a project so I can teach myself more about building rl systems. I’ve been considering working with the environment system from rlcard https://github.com/datamllab/rlcard/ but wonder if there are other more widely-used self play environment libraries. Thanks.
-
[Project] Making a Poker AI - having trouble with the form of ML to make smart / strong decisions
Can you point me to some active forums for poker bot building? I can only find github repo like https://github.com/datamllab/rlcard, which is mostly reinforcement learning. Whereas SoTA approach like Pluribus is more about game theory.
-
8+ Reinforcement Learning Project Ideas
Build a Poker bot with RLCard
-
What sort of algorithm should I use ? Incomplete information, card game. (Flowchart for reference)
Probably the easiest way for you to get started is to implement your game on an open source RL framework that has working implementations of some basic CFR variations as well as some other self-play algorithms such as NFSP. OpenSpiel and RLCard are two that I am aware of. Depending on the complexity of your game and how strong your agent needs to play, you might be satisfied with the performance you get using by one of these frameworks.
What are some alternatives?
mcts-general - General Python implementation of Monte Carlo Tree Search for the use with Open AI Gym environments.
gym - A toolkit for developing and comparing reinforcement learning algorithms.
Minigrid - Simple and easily configurable grid world environments for reinforcement learning
open_spiel - OpenSpiel is a collection of environments and algorithms for research in general reinforcement learning and search/planning in games.
crafter - Benchmarking the Spectrum of Agent Capabilities
mjai-reviewer - 🔍🀄️ Review mahjong game log with mjai-compatible mahjong AI.
Super-mario-bros-PPO-pytorch - Proximal Policy Optimization (PPO) algorithm for Super Mario Bros
Poker - Fully functional Pokerbot that works on PartyPoker, PokerStars and GGPoker, scraping tables with Open-CV (adaptable via gui) or neural network and making decisions based on a genetic algorithm and montecarlo simulation for poker equity calculation. Binaries can be downloaded with this link:
GoBigger - [ICLR 2023] Come & try Decision-Intelligence version of "Agar"! Gobigger could also help you with multi-agent decision intelligence study.
MonsterHunterPortable3rdHDRemake - Personal fork of a texture upscaling project for PSP's Monster Hunter Portable 3rd
shengji - An online version of shengji (a.k.a. tractor) and zhaopengyou (a.k.a. Finding Friends)
new-world-fishing-bot - user friendly python script who is able to catch fish in the game New World