Implemented with a simple min-max tree of two depth
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Updated
Nov 25, 2020 - HLSL
Implemented with a simple min-max tree of two depth
Artificial Intelligence for the game Go-Moku using the Minimax Algorithm with Alpha-Beta Pruning
🎮 使用α-β剪枝(Alpha-beta-pruning)的极小极大算法(Minimax-algorithm)实现的井字棋(一字棋、tic-tac-toe)游戏。
A generic JAVA implementation of the Minimax algorithm (and derivated...)
Minmax (minimax) algorithm with Alpha-Beta (𝛼−𝛽, ab) Pruning optimization for the Checkers (Draughts) game in Python 3. Same minimax algorithm works for chess, tic tac toe or similar games.
A board game framework, focused not on graphics or user interfaces, but on artificial players design, implementation and testing.
Halma game with an AI player, move validation, and dynamic board sizing
Othello/Reversi AI - minimax search with alpha beta pruning
Zero + is a Gomoku AI that implements threat space search, minimax with alpha beta pruning optimized with Zobrist and linear sequence cache, Principal Variation Search, and Monte Carlo Tree Search.
A c++ program to play tic-tac-toe with minimax tree. Try to beat and it ;-)
An advanced AI to play the 2-player board game Othello
minimax algorithm for chess with alpha-beta pruning
An AI for a modified Reversi version. The AI works with a game server that manages the game (https://github.com/marcluque/Reversi-Server)
Tic-Tac-Toe game written in Python and using pyGame; you can play versus another player or the computer on 2 difficulties: normal (random choices) and hard (minimax algorithm)
🥇 Unbeatable Tic Tac Toe game with a README contains very thing about MiniMax algorithms with explanation of it with c++ and js Implementation code
Lichess BOT engine
Chess AI using neural networks to predict move value
Game of isolation done as part of the Nanodegree program from Udacity
AI bot for the 2-player board game "Game of the Amazons"
Implementations of artificial intelligence agents that plays Pac-Man
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