Academic project for Principles & Applications of Artificial Intelligence course at Amirkabir University of Technology in Iran.
The Pac-Man projects were developed for CS 188. They apply an array of AI techniques to playing Pac-Man. However, these projects don’t focus on building AI for video games. Instead, they teach foundational AI concepts, such as informed state-space search, probabilistic inference, and reinforcement learning. These concepts underly real-world application areas such as natural language processing, computer vision, and robotics.
We designed these projects with three goals in mind. The projects allow you to visualize the results of the techniques you implement. They also contain code examples and clear directions, but do not force you to wade through undue amounts of scaffolding. Finally, Pac-Man provides a challenging problem environment that demands creative solutions; real-world AI problems are challenging, and Pac-Man is too.
- Search
- Multi-Agent Search
- Reinforcement Learning
- BNs and HMMs: Ghostbusters
- Machine Learning: Classification
The Pac-Man projects are written in pure Python 3.6 and do not depend on any packages external to a standard Python distribution.
Average score 86.5%