Implements multiple algorithms in the PAC Man game. https://inst.eecs.berkeley.edu/~cs188/su21/projects/

Search: https://inst.eecs.berkeley.edu/~cs188/su21/project1/#introduction

• Question 1: Finding a Fixed Food Dot using Depth First Search
• Question 2: Breadth First Search
• Question 3: Varying the Cost Function
• Question 4: A* search
• Question 5: Finding All the Corners
• Question 6: Corners Problem: Heuristic
• Question 7: Eating All The Dots
• Question 8: Suboptimal Search

Multi-Agent Search: https://inst.eecs.berkeley.edu/~cs188/su21/project2/

• Question 1: Reflex Agent
• Question 2: Minimax
• Question 3: Alpha-Beta Pruning
• Question 4: Expectimax
• Question 5: Evaluation Function

Reinforcement Learning: https://inst.eecs.berkeley.edu/~cs188/su21/project3/

• Question 1: Value Iteration
• Question 2: Bridge Crossing Analysis
• Question 3: Policies
• Question 4: Asynchronous Value Iteration
• Question 5: Prioritized Sweeping Value Iteration
• Question 6: Q-Learning
• Question 7: Epsilon Greedy
• Question 8: Bridge Crossing Revisited
• Question 9: Q-Learning and Pacman
• Question 10: Approximate Q-Learning

Machine Learning: https://inst.eecs.berkeley.edu/~cs188/su21/project5/

• Question 1: Perceptron
• Question 2: Non-linear Regression
• Question 3: Digit Classification
• Question 4: Deep Q-Learning