This is my homework for UC Berkeley CS188 (course archives), a course on Artificial Intelligence delivered by the University of California, Berkeley, and provided online by the EDX. I will complete this page as I continue following the courses’ archives.
For each project, a framework in Python was provided by the professor as a context to implement some AI. Students must implement key methods to fulfill specific requirements for the project (e.g. find the solution in fewer than 1000 iterations), and can fulfill optional objectives for a better grade (e.g. use fewer than 300 iterations). I don’t provide the source code of my implementation since it is supposed to be homework, but if you are personally interested in a specific algorithm, you can ask me for it (although there is nothing fancy in my answers, they do the job with a little optimization).
Project 1: Pacman search
One-Goal Problem – Big Level A* Search
Corners Problem – Medium Level A* Search
Food Problem (Multi-Pellet Problem) – Tiny Level A* Search
Food Problem – Tricky Level A* Search