Coursework for CSCI 561: Artificial Intelligence at USC 🤖
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Updated
Aug 7, 2018 - Java
Coursework for CSCI 561: Artificial Intelligence at USC 🤖
MinMax AI with Alpha-beta pruning for Othello board game
A project for the requirements of CS Intelligent Systems that lets a human play against an AI in Checkers. The agent uses Game Trees through Min/Max and Alpha-Beta Pruning.
Basic chess game, with the option to use a server or play against an AI(unfortunately the AI is an idiot)
Completed
Implementation of a min max algorithm in a bot that competes in the ultimate tic-tac-toe competition on theaigames.com
AI : Implementing algorithms for adversarial search strategies Min-Max and Alpha-Beta
Project in the ‘Data Structures’ Course of the Department of Electrical and Computer Engineering.
[ENSSAT-Project] Alpha-Beta AI that play tic tac toe.
Connect 4 game
Tic Tac Toe with a simple Artificial Intelligence based on the MiniMax algorithm, optimized with Alpha-Beta pruning.
A tic tac toe game with a minmax algorithm implementation.
AI Bases andorid Tic Tac Toe
A customizable chess game which allows you to play human vs human, computer vs human and computer vs computer. The computer AI is implemented through the MiniMax algorithm and enhanced with Alpha-Beta pruning.
Alpha Beta algorithm implementation for ConnectFour game.
This repository is to implement Othello board game allowing a player to play against AI Bot.
This is a java OOP of mastermind game and also includes an AI that use Knuth Algorithm to guess the code
USC 2021 Spring CSCI 561 Artificial Intelligence Score: A-
JavaFX GUI based TicTacToe with a AI MinMax opponent
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