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Lectures

The class meets on a Tuesday-Thursday schedule, from 1:00pm to 2:20pm in Salomon Center 001. 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!

Lecture recordings can be found here.
Date Topic Readings Slides
September 6th Introduction Chapters 1 and 2 Slides
September 11th Search Chapter 3 Slides
September 13th Game Theory (Gregory Carlin) Slides
September 18th Adversarial Search Chapter 5, up to and including 5.5. Slides
September 20th KRR-Logic Chapters 7 - 8 Slides
September 25th Uncertainty, Bayes Rule Chapter 13
September 27th Bayes Nets Chapters 13 and 14 (up to 14.4)
October 2nd Hidden Markov Models Chapter 15 (up to and including 15.3)
October 4th Midterm
October 9th Classical Planning Chapter 10
October 11th Robot Motion Planning Sections 25.4 - 25.6 (inclusive)
October 16th Probabilistic Planning Chapter 17 (up to and including 17.3)
October 18th Reinforcement Learning I Chapter 21 (up to and including 21.3)
October 23th Reinforcement Learning II
October 25th Machine Learning - Supervised Learning I Chapter 18
October 30th Machine Learning - Supervised Learning II
November 1st Unsupervised Learning I
November 6th Unsupervised Learning II
November 8th Advanced Topics: Natural Language Processing Chapter 23
November 13th Advanced Topics: Vision Chapter 24
November 15th Advanced Topics: Robotics Chapter 25
November 20th Advanced Topics: Algorithmic Game Theory (TBD)
November 27th Snippets of Research
November 29th Philosophy of AI Chapter 26, up to 26.2
December 4th Social and Ethical Issues Chapter 26.3
December 6th Slack
December 13th Final (2pm-4pm)