Trictrac

This is a game of Trictrac rust implementation.

The project is on its early stages. Rules (without "schools") are implemented, as well as a rudimentary terminal interface which allow you to play against a bot which plays randomly.

Training of AI bots is the work in progress.

Usage

cargo run --bin=client_cli -- --bot random

Roadmap

• rules
• command line interface
• basic bot (random play)
• [.] AI bot
• [] network game
• [] web client

Code structure

• game rules and game state are implemented in the store/ folder.
• the command-line application is implemented in client_cli/; it allows you to play against a bot, or to have two bots play against each other
• the bots algorithms and the training of their models are implemented in the bot/ folder

store package

The game state is defined by the GameState struct in store/src/game.rs. The to_string_id() method allows this state to be encoded compactly in a string (without the played moves history). For a more readable textual representation, the fmt::Display trait is implemented.

client_cli package

client_cli/src/game_runner.rs contains the logic to make two bots play against each other.

bot package

• bot/src/strategy/default.rs contains the code for a basic bot strategy: it determines the list of valid moves (using the get_possible_moves_sequences method of store::MoveRules) and simply executes the first move in the list.
• bot/src/strategy/dqnburn.rs is another bot strategy that uses a reinforcement learning trained model with the DQN algorithm via the burn library (https://burn.dev/).
• bot/scripts/trains.sh allows you to train agents using different algorithms (DQN, PPO, SAC).