Berkeley Pac-Man Projects 0, 1 & 2

This is a series of projects for the Winter 2020 Artificial Intelligence I course on DIT@UoA.

Project Tasks & Goals

Project 0:
Introductory Python tutorial, including Pac-Man Project 0 & an additional task of building a Priority Queue with an underlying min-Heap, using the heapq module.
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.