CSE 571 Artificial Intelligence

A simplified version of Go game in Python, with AI agents built-in and GUI to play.

Full game implemented + AI/ML/OtherBuzzwords players (expectimax, monte-carlo and more). Fork me!

Implementation of many popular AI algorithms to play the game of Pacman such as Minimax, Expectimax and Greedy.

Bots for the board game quoridor implemented using four algorithms: minimax, minimax with alpha beta pruning, expectimax and monte carlo tree search.

Solutions for the Projects of the Artificial Intelligence (CS 188) course of UC Berkeley

My solutions to projects 1, 2 & 3 of Berkeley's AI course

Ai agent for pacman

Pokémon battles simulator, with the use of MiniMax-Type algorithms (Artificial Intelligence project)

2048 game solved with Expectimax

Solutions to Pacman AI Multi-Agent Search problems

A multi-agent implementation of the game Connect-4 using MCTS, Minimax and Exptimax algorithms.

Final project of the course Introduction to Artificial Intelligence of NCTU

Implementation of reinforcement learning algorithms to solve pacman game. Part of CS188 AI course from UC Berkeley.

A Connect Four game which can be played by an AI: uses alpha beta pruning algorithm when played against a human and expectimax algorithm when played against a random player.

Some little games implementation, and also, machine learning implementation.

UC Berkeley CS188: Artificial Intelligence

👻 🎮 This is my implementation in the famous Berkeley pacman artificial intelligence project: http://ai.berkeley.edu/project_overview.html.

UC Berkeley CS188 Intro to AI -- Pacman Project Solutions

Contains a series of mini-projects based on UC Berkeley Pacman Projects & UArizona Hunt The Wumpus Project