Scripts for working with Pacman and Arch Linux

Agente del juego Pacman para la asignatura de Aprendizaje Automático

Pacman and Ghost Agent | Python | Artificial Intelligence | Search-based Algorithms | Learning-based Algorithms

PACMAN BERKELEY - CURSO DE INTELIGENCIA ARTIFICIAL UPF

AI agent playing PACMAN.

This repo was a short term project for CSCI 4511W (Artificial Intelligence) that uses a custom implementation of Pac-Man to compare different pathfinding algorithms.

Pacman coded in python (learning python)

Trabalho prático que aborda o desenvolvimento de uma versão do jogo Pacman.

This is the Pacman AI agent implemented as a search problem with DFS, UCS, BFS, A* with different heuristic functions. This project was a part of Artificial Intelligence Nanodegree @udacity.

Next generation community package management for Chakra.

Exploring Learning Algorithms with Pac-Man

CAP4621 - Artificial Intelligence HW 1

(Berkeley AI) Search problems arround PACMAN

Automatic Pacman Game using algorithms to find the way to pass

In this project, the Pac-Man agent finds paths through its maze world, both to reach a particular location and to collect food efficiently. Search algorithms such as Depth First Search, Bread First Search, Uniform Cost Search and A-star search are applied to Pac-Man scenarios.

In this project, agents are designed for the classic version of Pacman, including ghosts. Mini-max, Alpha-Beta pruning, Expectimax techniques were used to implement multi-agent pacman adversarial search.

A project that applies several Artificial Intelligence techniques such as informed state space search, reinforcement learning and probabilistic inference. Algorithms such as Depth First Search, Breadth First Search, Uniform Cost Search, A-star Search enabled the pacman to win in different game versions

Mini-max, Alpha-Beta pruning, Expectimax techniques are used to implement multi-agent pacman adversarial search.