:ghost: UC Berkeley CS188 Intro to AI -- The Pac-Man Projects

🕹️👻👾👻 In this thrilling AI adventure, we embark on a multi-stage quest to transform Pacman into an intelligent game-playing agent. Across three engaging projects, we explore various facets of artificial intelligence, from basic search algorithms to adversarial competition and reinforcement learning.

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.

The Pac-Man Projects from UC Berkeley Introduction to Artificial Intelligence course (CS188)

UC Berkeley's CS188: Introduction to Artificial Intelligence. This repository includes all the projects from the course, which combine to create an interactive Pac-Man game!

The Pac-Man AI Projects from UC Berkeley CS188 materials.

Three Pac-Man Projects of the UC Berkeley CS188 Introduction to Artificial Intelligence Course

Pacman project using the Berkely Pac Man framework.http://inst.eecs.berkeley.edu/ ~ cs188/pacman/ search.html

Implementation of the Q-Learning Algorithm for playing Pac-Man. Project based on the Berkeley CS188 intro to AI

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

:zap: My solutions to UC Berkeley CS188 Intro to AI -- The Pac-Man Projects

A comprehensive collection of classic and advanced search, game-tree, and heuristic algorithms in Python, combining AIMA-inspired implementations with the Berkeley CS188 Pac-Man search project.

Implementation of q-learning. Agents are tested for Gridworld, a robot simulator (Crawler) and Pac-Man. Based on the following project: https://inst.eecs.berkeley.edu/~cs188/fa18/project3.html

Lab exercise for lesson 7 from Artificial Intelligence Engineer Nanodegree by Udacity. This lab is possible thanks to the generous contributions of the UC Berkeley AI division and their work on the [Pac-Man Project](http://inst.eecs.berkeley.edu/~cs188/pacman/project_overview.html)

This project incorporates the development of an AI Pac-Man agent that includes classic search (A*, adversarial), reinforcement learning (MDP, Q-learning), and supervised machine learning for gameplay. Demonstrates progression from foundational search algorithms to advanced learning-based AI planning inspired by UC Berkeley CS188 course assignment.