This project implements a Pacman agent using the minimax algorithm with alpha-beta pruning and a custom evaluation function.

Fundamental of AI course which focuses on search, multiagents, mdp and reinforcement learning algorithms.

TicTacToe is a fun game, implemented using Minimax algorithm

this repository contains my codes for fundamentals of AI course projects

Kami dari kelas Kecerdasan Buatan D Kelompok 6 akan mengimplementasikan algoritma-algoritma yang telah diajarkan pada Final Project ETS kali ini

Artificial Intelligence

Artificial Intelligence and Machine Learning - Team Project - Dice Wars

Implements an agent to play Othello with adversarial search

Implementation of Udacity Nanodegree adversial search project using Monte Carlo Tree Search (MCTS). My implementation is a modification of the MCTS at "https://github.com/int8/monte-carlo-tree-search" to suit the project's knights isolation game. My implementation is in the "my_custom_player.py" file

Implemented a expectiminimax agent (2-ply search) with alpha – beta pruning and forward pruning (to reduce the branching factor in the game tree) to determine the best move give the state of the board.