Schedule

Date Topic Notes Reading Assignment out/due
1/8/2018 Introduction Course Introduction
  • A brief history of AI
  • AI in today's world
  • Course Details
  • In-Class Questionnaire
  • Agents and Their Problems
 Ch 2 ~ 3 Python/autograder Tutorial introduces you to Python and the autograder. Also look at official Python Tutorial.
1/10/2018 Uninformed Search Strategies Ch. 3.1 ~ 3.4 PA1 Out
1/15/2018 Martin Luther King Day
1/17/2018 Heuristic Search Strategies Ch 3.5 ~ 3.7
1/22/2018 Constraint Satisfaction Ch 6
1/25/2018 CSP II and Adversarial Search Ch 5 PA2 out
1/29/2018 Adversarial Search II Ch 5 PA1 Due
1/31/2018 Local Search Ch 4
2/5/2018 Planning Pllanning techniques Ch 10
2/7/2018 Probability Refresher and Review before Midterm Introduction to dealing with uncertainty; Ch 13.1 & 13.2 PA2 Due
2/12/2018 Midterm I
2/14/2018 Open
2/19/2018 President's Day
2/21/2018 Decision Making: MDPs
2/26/2018 Reinforcement Learning I Ch23 PA 3 out
2/28/2018 Reinforcement Learning II Q learning Ch 23
3/12/2018 Bayes Net I Ch 16
3/14/2018 Bayes Net II Ch 17 PA 3 Due; PA 4 out
3/19/2018 Project Proposal Presentation
3/21/2018 Reasoning over time Ch 15
3/26/2018 Machine Learning Introduction I PA 4 Due
3/28/2018 Machine Learning Introduction II
4/2/2018 Midterm II
4/4/2018 Machine Learning Introduction III Keynote
4/9/2018 Applications Modeling Human Behavior, Affective Computing and Virtual Humans
4/11/2018 Project Presentations
4/16/2018 Patriot's Day
4/18/2018 Project Presentations
4/24/2018 Project Reports Due Report and all code due at Midnigth - This is a hard deadline, no extensions


Important note: unless noted otherwise, all readings and assignments are due on the day that they appear in the schedule.

Unless noted otherwise, all readings are from Artificial Intelligence: A Modern Approach, 3rd Ed., Russell and Norvig.