CMSC 389: Artificial intelligence

Spring 2016

Prof. Blaheta

Artificial intelligence is in many ways a moving target. Once a problem is solved, or at least once its difficulties are somewhat understood, it is frequently no longer considered AI! Nevertheless, there are a few key areas that remain central to the idea of intelligence, and that feature heavily in AI textbooks. In this course, we will focus on three of them: problem space search, statistical reasoning, and neural networks. By the end of the course, you’ll be expected to know several of the main algorithms and frameworks for reasoning and learning, but more importantly, you’ll be expected to understand what makes them relevant, why a researcher might choose them, and where their strengths and weaknesses lie.

This class meets 12:30pm on TR.

The textbook is Russell and Norvig, Artificial intelligence: a modern approach, 3e. ISBN 978-0-13-604259-4

Course materials

Labs, homeworks, projects

Board photos