https://github.com/rmodi6/pacman-ai

Collection of Pacman AI solutions from the UC Berkeley AI course
https://github.com/rmodi6/pacman-ai

artificial-intelligence ghostbusters multiagent pacman python27 search

Last synced: 10 months ago
JSON representation

Collection of Pacman AI solutions from the UC Berkeley AI course

• Host: GitHub
• URL: https://github.com/rmodi6/pacman-ai
• Owner: rmodi6
• License: mit
• Created: 2020-01-14T18:40:59.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2020-01-14T19:19:15.000Z (about 6 years ago)
• Last Synced: 2025-02-10T15:51:01.644Z (about 1 year ago)
• Topics: artificial-intelligence, ghostbusters, multiagent, pacman, python27, search
• Homepage:
• Size: 3.91 KB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# pacman-ai

![Pacman-AI](https://rmodi6.github.io/images/pacman-ai.gif) 

This repository contains solutions to the Pacman AI Search, Multiagent and Ghostbusters problems from UC Berkeley's CS188 Intro to AI Pacman projects [page](http://ai.berkeley.edu/project_overview.html).

## pacman-ai-search

The search problem includes implementation of uninformed search algorithms like depth-first search (DFS), breadth-first search (BFS), uniform cost search, and A star search algorithms. These algorithms are used to solve navigation and traveling salesman problems in the Pacman world.

## pacman-ai-multiagent

The multiagent problem requires modeling an adversarial and a stochastic search agent using minimax algorithm with alpha-beta pruning and expectimax algorithms, as well as designing evaluation functions.

## pacman-ai-ghostbusters

The ghostbusters problem involves designing a Pacman agent that uses sensors to locate and eat invisible ghosts. It includes implementation of exact inference in a bayesian network using the forward algorithm.