Outline
Lecture 0: Articial intelligence
Lecture 1: Intelligent agents
Lecture 2: Solving problems by searching
Lecture 3: Constraint satisfaction problems
Lecture 4: Adversarial search
Lecture 5: Representing uncertain knowledge
Lecture 6: Inference in Bayesian networks
Lecture 7: Reasoning over time
Lecture 8: Making decisions
Lecture 9: Learning
Lecture 10: Communication
Lecture 11: Articial General Intelligence and beyond
3 / 11
Philosophy
Thorough and detailed
Understand the landscape of articial intelligence.
Be able to write from scratch, debug and run (some) AI algorithms.
Well established algorithms and state-of-the-art
Well-established algorithms for building intelligent agents.
Introduction to materials new from research ( 5 years old).
Understand some of the open questions and challenges in the eld.
Practical
Fun and challenging course project.
≤
4 / 11
Lectures
Theoretical lectures
Exercise sessions
5 / 11
