This course introduces artificial intelligence theory and practice underlying expert systems. Topics include: knowledge bases, inference engines, knowledge representation formalisms, knowledge acquisition, search and reasoning techniques, and other practical issues in the development of expert systems. For logic based approaches, it covers rule-based systems, semantic networks, frames, and mixed representation formalisms. For uncertainty management, it covers certainty factors, Bayesian network, D-S belief functions, and fuzzy logic.
Prerequisite: COMP 371