Lecture: Artificial Intelligence

Artificial intelligence has permeated almost every aspect of our lives, from content recommendation and healthcare to predictive policing and autonomous driving, affecting everyone, everywhere, all the time. As the demand for AI specialists grows, so does the need for students who can develop and apply new AI technologies.

This course is an introduction to the field of Artificial Intelligence and introduces the fundamental ideas and techniques that underpin the design of intelligent machines. By the end of this course, you will have learned how to design autonomous (software) agents that efficiently make decisions in fully informed, partially observable, and adversarial environments, and how to optimize actions in uncertain sequential decision environments to maximize expected profit.


Course content (subject to change):

  • Informed search
  • Uninformed search
  • Constraint Satisfaction Problems
  • Adversarial search
  • Markov Decision Processes
  • Reinforcement Learning
  • Local search and Optimization