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

The Pacman Projects by the University of California, Berkeley.

Search algorithms(BFS, DFS, UCS, A*) in python.Berkeley Pacman Project 1.

Solutions of 1 and 2 Pacman projects of Berkeley AI course

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

UC Berkeley Pacman Project

My implementation for Berkeley AI Pacman projects No. 1 and No. 2

my solution for UC Berkeley AI projects pacman

Pacman AI Projects 1,2,3 - UC Berkeley

Berkeley AI Pacman Project for developing search agents to play Pacman

Python3 version of UC Berkeley's CS 188 Pacman Capture the Flag project

Solution to some Pacman projects of Berkeley AI course

Team Project for Berkeley's Pacman Capture The Flag Competition

This is the second project of the Spring 2014 CS 188 (Introduction to Artificial Intelligence) class at UC Berkeley. It implements a pacman who can play against adversarial agents with dynamic tree look up (both Minimax and Expectimax). it optimizes tree lookup with AlphaBetaPruning and finally contains a master strategy in the form of the betterEvaluationFunction (in multiAgents.py) for evaluating each state in the tree.

This is an implementation of intelligent pacman agents for the Pacman Capture the Flag game designed at UC Berkeley. I worked on this project with Liyuan Zheng.

Pacman, AI Projects of Berkeley University (SOLUTIONS)

Pacman projects implemented in Python (from Berkeley Courses)

My solutions to the Berkeley Pac-Man projects of spring 2022.

Berkeley Pac-Man 🤤◽◽◽👻 projects 0, 1 & 2 solutions

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

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

Berkeley Pacman Projects (1 and 2), Depth First Search, Breadth First Search, Uniform Cost Search ,A* Search , Heuristic Functions ,Suboptimal Search, Minimax Algorithm, Alpha-Beta Pruning, Expectimax, Constraint Santisfaction Problems, RLFA CSP problem, Propositional Logic, First-order Logic

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.

AI Project Spring 2023: The Pac-Man Project from Berkeley's Intro to AI course

AI pacman project(berkeley university) - Fall 2021

My solution to Berkeley's AI Pacman project

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).

My solutions to the UC Berkeley AI Pacman Projects

UC Berkeley CS188 Intro to AI -- Pacman Project Solutions