• Implemented BFS, DFS, A*, Hill Climbing, Genetic Algorithm and Monte Carlo Tree Search on Berkeley Pacman AI game resulting in Pacman winning on it’s own in case of some algorithms
• Built a perceptron classifier to learn from recorded Pacman games as training algorithms, and ran the classifier to determine which action would be taken by the observed agent
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).