Yugioh AI uses large language models (LLM) and RL to play Yu-Gi-Oh. It is inspired by [yugioh-ai](https://github.com/melvinzhang/yugioh-ai]) and [yugioh-game](https://github.com/tspivey/yugioh-game), and uses [ygopro-core](https://github.com/Fluorohydride/ygopro-core).
YGO Agent is a project to create a Yu-Gi-Oh! AI using deep learning (LLMs, RL). It consists of a game environment and a set of AI agents.
## Usage
### Setup
## ygoenv
`ygoenv` is a high performance game environment for Yu-Gi-Oh! It is initially inspired by [yugioh-ai](https://github.com/melvinzhang/yugioh-ai]) and [yugioh-game](https://github.com/tspivey/yugioh-game), and now implemented on top of [envpool](https://github.com/sail-sg/envpool).
An automated setup script is provided for Linux (tested on Ubuntu 22.04). It will install all dependencies and build the library. To run it, execute the following commands:
## ygoai
`ygoai` is a set of AI agents for playing Yu-Gi-Oh! It aims to achieve superhuman performance like AlphaGo. Currently, only a RL-based agent is implemented.
You should see text output showing two random AI playing a duel by making random moves.
You can set `--seed` to a fixed value to get deterministic results.
## Implementation
The implementation is initially based on [yugioh-game](https://github.com/tspivey/yugioh-game). To provide a clean game environment, it removes all server code and only keeps basic duel-related classes and message handlers.
To implement the AI, inspired by [yugioh-ai](https://github.com/melvinzhang/yugioh-ai]), every message handler also provides all possible actions that can be taken in response to the message.
