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CSE 571 Artificial Intelligence

Python 100.00%
artificial-intelligence a-star-search uniform-cost-search depth-first-search breadth-first-search greedy-search neural-networks minimax-algorithm alpha-beta-pruning expectimax

artificial-intelligence-pac-man's Introduction

Artificial-Intelligence-Pacman-Project

Arizona State University

CSE 571 Artificial Intelligence

Fall 2017

Grade A-

In this project, several techniques of Artificial Intelligence such as Searching, Adversarial Behaviour, Deep Reinforcement Learning, Neural Network etc are implemented to help the pacman agent to maximize its expected utility.

  • Project 0: Python Autograder Tutorial
  • Project 1: Searching - DFS, BFS, UCS, Greedy Search, A* Search, etc.
  • Project 2: MultiAgent Pacman - minimax, alpha-beta pruning, expectimax, etc.
  • Project 3: Reinforcement Learning - MDP, value iteration, q-learning, epsilon-greedy, approximate q-learning, etc.
  • Project 4: Ghostbusters - HMM, Particle Filtering, Bayes' Nets, Deep Reinforcement Learning, etc.

Refer project specification file under each project for more details.

Programming Language - Python 2.7

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