Berkeley_Pacman_Project

Implementation of Berkeley's Pacman Project as a part of Artificial Intelligence course. Winter 2020

Project 1:

• Pac-Man Project 1, focused on Search Algorithms, modelling Problem States & Heuristic Functions
• DFS
• BFS
• Uniform-Cost Search
• A* Search
• Specific Problem (navigation, travelling salesman) modelling (starting state, goal state check, creating successor states)
• Implementing & Experimenting with Heuristic Functions (admissable, optimal, greedy)

Project 2:

• Pac-Man Project 2, focused on Multi-Agent Search Algorithms & implementing Evaluation Functions.
• Dummy Reflex Agent
• MiniMax
• Alpha-Beta Pruning
• Expectimax
• Implementing a custom Evaluation Function by experimenting & tuning on the considered parameters and their weights.