Artificial Intelligence

Catalog description

Credits 3. 3 Lecture Hours. Fundamental concepts and modern methods of artificial intelligence; search (uninformed, informed, iterative improvement, constraint satisfaction, space/time complexity); game playing: minmax, alpha-beta pruning; knowledge representation and reasoning; propositional logic, first-order logic and automated theorem proving, etc.; planning; uncertainty and probabilistic reasoning; machine learning and deep learning basics; selected topics include cognitive models, distributed AI, intelligent agents, perception, robotics, natural language, etc.; philosophical issues, including ethics. Prerequisites: CSCE 411 or approval of instructor; graduate classification.