Course Category:
Department Elective Course
An overview of the main thrusts in artificial intelligence, starting with the historically symbolic, logic-based approaches to knowledge representation, planning, reasoning and learning, leading into more recent directions of statistics-based probabilistic approaches (such as Bayesian approaches, belief nets, probabilistic reasoning, etc.). The course also touches on more recent developments in natural language processing, visual processing, robotics, machine learning, and philosophical foundations.
