Quoridor AI based on Monte Carlo tree search
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Updated
May 18, 2024 - JavaScript
Quoridor AI based on Monte Carlo tree search
A fast C++ impementation of Monte Carlo Tree Search with abstract classes that a user of this library can extend in order to use it. To demonstrate it I apply it to the game of Quoridor.
Bots for the board game quoridor implemented using four algorithms: minimax, minimax with alpha beta pruning, expectimax and monte carlo tree search.
A terminal implementation of the game Quoridor with an engine
An iOS game develop with SwiftUI & Firebase in MVVM with so many excellent features!UI refer to STARLUX、Pokémon GO and Instagram. User could login with many social media accounts and play Quoridor with others on Internet.
A terminal-based engine simulating the board game Quoridor, featuring player movement, wall placement, and a simple AI opponent. 🎲
AlphaZero-style Quoridor engine trained from zero knowledge — no human games, no heuristics. 24 h of self-play on one consumer GPU, after which it beats the previous strongest public Quoridor AI with no search at all. Play it in your browser.
First two labs for GameDev Course
Quoridor game implementation integrated with a versatile and reusable AI agent for solving two-player board games
A Quoridor implementation in Rust, including different AIs
A simple minmax AI for the board game Quoridor.
A Framework with multiple applications around Quoridor.
The first repository
Superhuman AlphaZero-style Quoridor engine: batched MCTS in Rust, honest self-play training. Play it & analyze your games at claustrophobia.dev
This homework is about Implementing a smart agent to play Quoridor, using Min-max, a heuristic function, Transposition Table and forward pruning. This homework is a part of many projects in a Fundamentals to AI course @ FUM.
A Quoridor game with a html/js frontend and a rust backend
A 3D Quoridor (wall chess) board game for Android — offline vs-AI and pass-and-play, built in Flutter with a custom Dart 3D renderer.
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