AI Pacman Multiagents

files from Artificial Intelligence algorithms class from UC Berkeley spring 2013 using python - multi agents solution search applied to a pacman game

Designd agents for the classic version of Pacman, including ghosts. Implement both minimax and expectimax search.

UC Berkeley AI Pacman multiagents game solution

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Intro to AI Project 2 - Multi-Agent Pacman

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Pacman AI Project Search and multiAgents files are redone

Implementation of assignment 2 of the Berkeley AI pacman problems - multi agent search.

Automatic Pacman Game using AI algorithms, major code in multiAgents.py

Pacman implementation using multiagents approach. Contents and initial code from: http://ai.berkeley.edu/multiagent.html

An implementation of the Multi-Agent Search Project from Berkeley AI (http://ai.berkeley.edu/multiagent.html). The multiAgents.py file implements a better pacman agent, and the ghostAgents.py file implements new classes of ghosts agents.

This is a UC Berkeley's AI exercises for making PACMAN searching algorithms optimized. (DFS, BFS, UCS, A*, food heuristics etc). Files that I update is search.py, multiAgents.py and search.py. It also includes an autograder to check the results (python autograder.py). My results after the exercise was 32/31 (+1 for a bonus point).