Topics include search, game playing, knowledge representation, inference, planning, reasoning under uncertainty, machine learning, robotics, perception, and language understanding. Prerequisites: COMPSCI 61A, COMPSCI 61B, and COMPSCI 70.

The course follows the chapters of the classic AI textbook Artificial Intelligence: A Modern Approach, covering topics such as search pruning, constraint satisfaction problems, Markov decision processes, reinforcement learning, Bayesian networks, Hidden Markov Models, as well as fundamental concepts in machine learning ...

Office hours: Monday 4:30-5:30, Tuesday 4:30-5:30pm (730 Sutardja Dai Hall aka the Newton Room---if you keep going straight when exiting 7th floor elevators, it'll be on your right after having gone through 3 doors.