COMP-424: Artificial Intelligence (Winter 2017)
Term: Winter 2017.
Course syllabus (last updated Aug.31 2016) includes info on TAs, office hours, contact information.
- IMPORTANT: NEW PRE-REQ! At least one university level course in probability and/or statistics, e.g. MATH-203, MATH-323, ECSE-305. Students who have not satisfied this requirement will NOT be admitted into the course for Winter 2017.
We will cover selected topics in Artificial Intelligence. We will study modern techniques for computers to make good (in some cases optimal) decisions that are applicable throughout
an enormous range of industrial, civil, medical, financial, robotic and
information systems. We will not attempt to cover the entire range of AI sub-areas in detail, but will survey several key themes.
IMPORTANT: The schedule is subject to change.
Up-to-date information about the schedule and assigned readings will
be posted on the class web page.
- Introduction to AI. Brief history. Different agent architectures.
- Search: uninformed and heuristic search, A*, local search and optimization.
- Constraint satisfaction problems.
- Game playing and adversarial search.
- Knowledge representation. Logical reasoning. Propositional logic.
- Planning algorithms.
- Reasoning under uncertainty. Bayes rule. Belief networks.
- Decision making. Utility theory. Reinforcement learning. Game theory.