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 5.0-5.2

R&N slides on Game Playing 

Introduction on Piazza

Start-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 paper

R&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 4

R&N slides on Beyond Search

2: Tri-directional search released

Feb 11

5

Feb 5

4. Constraint Satisfaction; Chapter 6

R&N slides on Constraint Satisfaction Problems

2: Tri-directional search due

Feb 11

6

Feb 12

5. Probability; Chapter 13

R&N slides on Probability

3: Bayes Nets Sampling released

Feb 25

7

Feb 19

6. Bayes Nets; Chapter 14

R&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, 20.1-20.2

R&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 Exam

Topics List

Midterm Exam

Mid-Course Survey

Mar 5 - 11

10

Mar 12

7. ML to end; Chapter 18.6-18.11; Mitchell reading on EM; Chapter 20.3

R&N slides on Neural Nets.  Tutorial slides on boosting; Boosting paper

Mar 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 15

R&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 22

R&N slides for Speech and Grammar

6: HMMs released

Apr 22

14

Apr 9

9. Logic & Planning; Chapter 7-10

R&N slides   Chapter 7, Chapter 8, Chapter 9, Chapter 11, Chapter 12

15

Apr 16

10. Planning under Uncertainty; Chapter 17, Chapter 21

R&N slides  Chapter 17

6: HMMs due

Apr 22

16

Apr 23

Final Exam Week

Topics List

Final Exam Starts

End 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.