A Multi-threaded Implementation of AlphaZero
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Updated
Jan 7, 2023 - Python
A Multi-threaded Implementation of AlphaZero
A pytorch based Gomoku game model. Alpha Zero algorithm based reinforcement Learning and Monte Carlo Tree Search model.
Artificial Intelligence for the game Go-Moku using the Minimax Algorithm with Alpha-Beta Pruning
♟♟♟♟♟ A Gomoku game AI based on Monte Carlo Tree Search, can be trained on policy-value network now. 一个蒙特卡洛树搜索算法实现的五子棋 AI,现可用神经网络训练模型。
gomoku Game Implemented in the Go Language Using WebSocket
An integrated interactive go-game system.
A gomoku game implements with PyGame
5 in a row game for Ethereum written in Solidity
Minimalistic HTML5 Gomoku Written in ES6 - AI Under Development
Android frontend application featuring the Gomoku strategy board game built using Jetpack Compose
A Gomoku developed with Qt. 一個基於Qt開發的五子棋
A simple Gomoku game using React/Typescript
Gomoku is a game which is played on Go board. The objectives of the project is to develop an agent capable to beat human player. Across the project we tackle minimax algo, heuristic function, optimization and user interface.
A simple search agent for playing Gomoku using the minimax algorithm with alpha-beta pruning.
Gomoku (Five in a row) game. Set the size of the board and the winning criteria as you like. Play online.
Interactive web app featuring the Gomoku strategy board game powered by React and Spring MVC
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