Artificial Intelligence project designed by UC Berkeley. Designed game agents for the game Pacman using basic, adversarial and stochastic search algorithms, and reinforcement learning concepts

Implemented various AI algorithms in Pac-Man projects developed by UC Berkeley. Implemented informed/blind state-space search using search algorithms like BFS, DFS, UCS and A* algorithm with heuristic calculation. Designed an algorithm for reflex agent, minimax and alpha-beta pruning. Reinforcement Learning using MDP (Value Iteration and Policy Evaluation) - Implemented Markov Decision process using Value iteration in the Pacman World. Designed perceptron classifier for data classification. Developed applications using python. http://ai.berkeley.edu/project_overview.html

my solution for UC Berkeley AI projects pacman

Pacman AI Projects 1,2,3 - UC Berkeley

Deep learning project on top of UC Berkeley's (http://ai.berkeley.edu) Pacman source-code.

UC Berkeley CS188 Projects # Licensing Information: You are free to use or extend these projects for # educational purposes provided that (1) you do not distribute or publish # solutions, (2) you retain this notice, and (3) you provide clear # attribution to UC Berkeley, including a link to http://ai.berkeley.edu. # # Attribution Information: The Pacman AI projects were developed at UC Berkeley. # The core projects and autograders were primarily created by John DeNero # (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu). # Student side autograding was added by Brad Miller, Nick Hay, and # Pieter Abbeel (pabbeel@cs.berkeley.edu).

Licensing Information: You are free to use or extend these projects for educational purposes provided that (1) you do not distribute or publish solutions, (2) you retain this notice, and (3) you provide clear attribution to UC Berkeley, including a link to http://ai.berkeley.edu. Attribution Information: The Pacman AI projects were developed at UC Berkeley. The core projects and autograders were primarily created by John DeNero (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu). Student side autograding was added by Brad Miller, Nick Hay, and Pieter Abbeel (pabbeel@cs.berkeley.edu).

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.

My solutions to the UC Berkeley AI Pacman Projects

UC Berkeley CS188 Intro to AI -- Pacman Project Solutions

UC Berkeley Pacman AI Projects

UC Berkeley CS188 Intro to AI Pacman Projects

AI project designed by UC Berkeley. Designed reflex and minimax agents for the game Pacman.

UC Berkeley AI Pacman Project

PACMAN AI project from UC Berkeley

No description available

伯努利大学的吃豆人项目，具体实现方法和代码逻辑见代码文档，效果还不错，跑分可以

Project 1: Search from UC-Berkeley famous Pacman Project

My solutions to the UC Berkeley Pacman AI assignment: http://ai.berkeley.edu/project_overview.html

An Artificial Intelligence Project based on UC Berkeley's Pacman AI course

Pacman project for the Fundamentals of AI of the Advanced Master of AI at KULeuven. Project originally designed by UC Berkeley.

This project is based on the UC Berkeley CS188 Pacman AI framework, implementing and testing algorithms and multi-agent search strategies for Pacman.

this is the second pacman project for course AI of UC Berkeley done as the second project of course AI basics and applications of AUT

My solutions to the course project for my university AI course, which was based on the pacman challenges used by UC Berkeley

A Python implementation of a Pacman agent, which can play autonomously using Bayesian inference and ghost sensors. Project designed at UC Berkeley. http://ai.berkeley.edu/home.html

My solutions to the UC Berkeley AI Pacman Projects. Search: Implement depth-first, breadth-first, uniform cost, and A* search algorithms. These algorithms are used to solve navigation and traveling salesman problems in the Pacman world.

A Python project using reinforcement learning to enhance Pacman’s gameplay. Developed from UC Berkeley’s AI curriculum, it features Q-learning, custom feature extraction, and performance analysis across layouts.

This is my final project for the Artificial Intelligence course (CIE 458) in UST - Zewail City. This is project is prepared by UC Berkeley, as part of their course CS 188. In this project I implemented some of AI search algorithms such as minimax , Alpha & Beta and expectimax search and try to designing my evaluation function in a simulation for Pacman game.

Pacman Artificial Intelligence Python project for UC Berkeley CS188 Intro to AI

UC-Berkeley-AI-Pacman-Project