This course introduces algorithms and techniques in artificial intelligence, with particular emphasis on reasoning in uncertain environments and machine learning with human feedback and/or limited training examples. The topics include AI-based searching algorithms, reinforcement learning, knowledge representation, uncertainty reasoning, planning and acting. The list of topics aims to provide first-principles understanding of modern AI applications including computer game, robotics and natural language processing.

For a student to pass the course, at least 30% of the maximum mark for the examination must be obtained.