Preliminary Calendar for Artificial Intelligence (Spring 2018)

Last Revised: 01/08/18

Please check this page frequently for updates!  Chapters refer to the textbook Artificial Intelligence: A Modern Approach (3rd edition) by Russell and Norvig (R&N).  See Further Information for optional readings and videos for each section.

 Week # Week Of Lessons/Study Material Assignment/Exam Due Date** 1 Jan 8 1. Game Playing through Depth-limited Search; review/learn Python; play each other in Isolation; Chapter 1-2; Chapter 5.0-5.2R&N slides on Game Playing Introduction on PiazzaStart-of-Course Survey Jan 14 2 Jan 15 1. Game Playing through end; Chapter 5.3-5.9, Korf: 3 player alpha-beta 1: AI Isolation Player released Jan 28 3 Jan 22 2. Search;  Chapter 3; Korf paperR&N slides on Uninformed Search and Informed Search 1: AI Isolation Player due Jan 28 4 Jan 29 3. Simulated Annealing and Local Search; Chapter 4R&N slides on Beyond Search 2: Tri-directional search released Feb 11 5 Feb 5 4. Constraint Satisfaction; Chapter 6R&N slides on Constraint Satisfaction Problems 2: Tri-directional search due Feb 11 6 Feb 12 5. Probability; Chapter 13R&N slides on Probability 3: Bayes Nets Sampling released Feb 25 7 Feb 19 6. Bayes Nets; Chapter 14R&N slides on Bayes Nets and Bayes Nets Inference 3: Bayes Nets Sampling due Feb 25 8 Feb 26 7. ML through Random Forests; Chapter 18.1-5,18.8, 20.1-20.2R&N slides on Learning from Observation: Decision Trees (18.1-18.3); R&N slides Statistical Learning (20.1-20.2)On-campus slides on Decision Trees and the accompanying alternative explanation.  For those interested in a practical use of Decision Trees that may be on your Android phone by now, see Clawson’s PhD dissertation. 4: Decision Trees and Forests released Mar 18 9 Mar 5 Midterm ExamTopics List Midterm ExamMid-Course Survey Mar 5 - 11 10 Mar 12 7. ML to end; Chapter 18.6-18.11; Mitchell reading on EM; Chapter 20.3R&N slides on Neural Nets.  Tutorial slides on boosting; Boosting paperMar 14 is the withdrawal deadline! 4: Decision Trees and Forests due Mar 18 11 Mar 19 Spring Break Week 5: Expectation Maximization released Apr 1 12 Mar 26 8. Pattern Recognition through Time through New Observation Sequence for “We”; Chapter 15R&N slides for Temporal probability models: HMMs and Kalman filters 5: Expectation Maximization due Apr 1 13 Apr 2 8. Pattern Recognition through Time to end; Chapter 1 “The Fundamentals of HTK”; Chapter 22R&N slides for Speech and Grammar 6: HMMs released Apr 22 14 Apr 9 9. Logic & Planning; Chapter 7-10R&N slides   Chapter 7, Chapter 8, Chapter 9, Chapter 11, Chapter 12 15 Apr 16 10. Planning under Uncertainty; Chapter 17, Chapter 21R&N slides  Chapter 17 6: HMMs due Apr 22 16 Apr 23 Final Exam WeekTopics List Final Exam StartsEnd of Course Survey & CIOS! Apr 23 - 29

** - All assignments are due at midnight UTC-12 on the date specified (that is, at the end of the day on Sunday). UTC-12 is “anywhere on earth”, meaning that if it is still before midnight anywhere on earth, the assignment will still be accepted. Generally, this translates to sometime Monday morning in the Western hemisphere and Monday afternoon or evening in the Eastern hemisphere. To see due dates in terms of your local time, change your timezone in T-Square.

** - Topic lists for the exams are also subject to change if need be. Will be final one week before the exam.