Vintage Pacman Game developed in Flutter

Solutions of 1 and 2 Pacman projects of Berkeley AI course

Solution to some Pacman projects of Berkeley AI course

Team Project for Berkeley's Pacman Capture The Flag Competition

Principles & Applications of Artificial Intelligence at Amirkabir University of Technology course projects

Reinforcement Learning Course Project - IIT Bombay Fall 2018

multi-agent moving target pursuit in an unknown 4-connected grid world with persistent coverage planning

Pacman and Ms. Pacman reverse engineered in JavaScript

Pacman using c++ and Computer Graphics.

Explore foundational AI concepts through the Pac-Man projects, designed for UC Berkeley's CS 188 course. Implement search algorithms, multi-agent strategies, and reinforcement learning techniques in Python, emphasizing real-world applications. Engage in the Eutopia Pac-Man contest for a multiplayer capture-the-flag challenge

👻 UC Berkeley CS188 Intro to AI -- The Pac-Man Projects

A Monte-Carlo Tree Search mathod that enables two agents interact and work together in the game of Pacman Capture the Flag.

Berkeley Pacman Projects (1 and 2), Depth First Search, Breadth First Search, Uniform Cost Search ,A* Search , Heuristic Functions ,Suboptimal Search, Minimax Algorithm, Alpha-Beta Pruning, Expectimax, Constraint Santisfaction Problems, RLFA CSP problem, Propositional Logic, First-order Logic

Berkeley Pac-Man 🤤◽◽◽👻 projects 0, 1 & 2 solutions

C'est un projet PacMan

A simple PACMAN game developed in Borland C Graphics lib. (code copied from web)

I have completed four Pacman projects of the UC Berkeley CS188 Intro to Artificial Intelligence course. The Pac-Man projects were developed for CS 188. They apply an array of AI techniques to playing Pac-Man. They teach foundational AI concepts, such as informed state-space search, probabilistic inference, and reinforcement learning.

University of Oulu A.I. coursework, Pacman projects. Original materials are offered by UC Berkeley.

UC Berkeley Pacman AI Projects

Design and Implementation of Random Forest algorithm from scratch to execute Pacman strategies and actions in a deterministic, fully observable Pacman Environment.