CS 1410

Artificial Intelligence

Lectures

The class meets on a Tuesday-Thursday schedule, from 1:00pm to 2:20pm in List 120. Note that the schedule below is tentative, and may be revised as we go along.

Resources

Required Text

Artificial Intelligence: A Modern Approach, Stuart Russell and Peter Norvig. Be sure to check for errata! (scroll down for a list of current errata)

Lecture recordings are available on Panopto.
Date Topic Homework Slides
September 7th Introduction Read chapters 1 and 2 Slides
September 12th Search: View pre-recorded lecture, no class Read chapter 3 Slides
September 14th Game Theory (Vince Kubala) Slides
September 19th Adversarial Search Read chapter 5, up to and including 5.5. Slides
September 21st KRR-Logic Chapters 7 - 8. Slides
September 26th Uncertainty, Bayes Rule Chapter 13 Slides
September 28th Bayes Nets (Nakul Gopalan) Chapters 13 and 14 (up to 14.4). Slides
October 3rd Hidden Markov Models Chapter 15 (up to and including 15.3) Slides
October 5th Midterm
October 10th Classical Planning Chapter 10. Slides
October 12th Robot Motion Planning Sections 25.4 - 25.6 (inclusive) Slides
October 17th Probabilistic Planning Chapter 17 (up to and including 17.3) Slides
October 19th Reinforcement Learning I Chapter 21 (up to and including 21.3) Slides
October 24th Reinforcement Learning II Slides
October 26th Machine Learning - Supervised Learning I Chapter 18. Slides
October 31st Machine Learning - Supervised Learning II Slides
November 2nd Unsupervised Learning I Slides
November 7th Unsupervised Learning II Slides
November 9th Advanced Topics: Natural Language Processing Chapter 23 Slides
November 14th Advanced Topics: Vision Chapter 24 Slides
November 16th Advanced Topics: Robotics Chapter 25 Slides
November 21st Advanced Topics: Algorithmic Game Theory (Enrique Areyan) Slides
November 28th Snippets of Research Slides
November 30th Philosophy of AI Chapter 26, up to 26.2 Slides
December 5th Social and Ethical Issues Chapter 26.3 Slides
December 14th Final