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game-player

This crate provides the base components for implementing a player in a two-person game.

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Overview

The game-player crate provides the core traits and search components needed to build a player for a two-person game.

It provides:

  1. A min-max game tree search algorithm using alpha-beta pruning and transposition tables for optimal performance.
  2. A Monte Carlo Tree Search algorithm with UCT-based selection, pluggable value estimation (ValueEstimator — random playouts, static evaluation, or any other strategy), configurable initial-value weighting, and eager or lazy child expansion.

Documentation

  • User's Guide — overview of the library, criteria for choosing a search algorithm, an explanation of the minimax search, and a walkthrough of a complete tic-tac-toe player.
  • API referencecargo doc --open.
  • Runnable exampleexamples/tic_tac_toe.rs, via cargo run --example tic_tac_toe.

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Base component library for implementing a player for two-person games

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