A .NET Othello game.
-
Updated
Jan 10, 2022 - C#
A .NET Othello game.
Project using minmax and alpha beta pruning to make ai for tictactoe and connect4 with gui using pygame
Used min-max alpha-beta pruning algorithm to make an AI (easy, medium, hard), implemented on the server-side with Django Rest-Framework. Used Angular for frontend.
Ultimate Tic-Tac-Toe against AI
An implementation of AI player for Gomoku.
This is a project that plays a professor's version of SuperTicTacToe against you (or other robots) and should win every time (it does not). It uses a minmax algorithm with alpha beta pruning.
AI player of the game 2048 (expectiminimax + alpha-beta pruning + iterative deepening search)
This project is a Python implementation of the classic Pacman game, using the MinMax algorithm for decision making.
AI project bagh-chal game implemented using min-max algorithm
A minmax based tic-tac-toe game for a school project.
Alpha Beta algorithm implementation for ConnectFour game.
The game "Three in a row" with a GUI and an unbeatable engine.
Minimax, Alpha-beta Pruning, Expectimax를 활용한 Multi-Agent 구현
Porjects for Algorithmic Techniques for Artificial Intelligence
Link Presentation : https://youtu.be/JfNR6zEKbc4
Connect Four game for Android with optional AI opponent
Add a description, image, and links to the minmax-alpha-beta-pruning topic page so that developers can more easily learn about it.
To associate your repository with the minmax-alpha-beta-pruning topic, visit your repo's landing page and select "manage topics."