dawnduan / intro-to-artificial-intelligence-winter-2017

csc384

Overview: Theories and algorithms that capture (or approximate) some of the core elements of computational intelligence. Topics include: search; logical representations and reasoning, classical automated planning, representing and reasoning with uncertainty, learning, decision making (planning) under uncertainty. Assignments provide practical experience, in both theory and programming, of the core topics.

Topics:

1. Search (Uninformed, Heuristic, Game-tree)
2. Logical representations and reasoning (Constraint Satisfaction Problems, Knowledge Rrepresentation)
3. Representing and reasoning with uncertainty. (Bayesian Networks)