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.