CSE 573 - Artificial Intelligence I- Autumn 2001

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Overview Instructor: Henry Kautz Office: 417 Sieg Hall Office hours: Monday 2-3pm or by appointment Teaching Assistant: Don Patterson Office: 429 Sieg Hall Office hours: Wednesday 11:30-12:30 or by appointment You can also ask questions to the class via the mailing list. Send mail to the mailing list. Text: Stuart Russell & Peter Norvig, Artificial Intelligence: A Modern Approach Chess Tournament: HTML Syllabus: PS, PDF Lecture notes: Lecture 1 posted 10/1/01: Power Point Power Point translated to Rich Text Format Power Point translated to Hyper Text Lecture 2 posted 10/3/01: Power Point Power Point translated to Rich Text Format Power Point translated to Hyper Text Revised Lecture 2 posted 10/8/01: Power Point Power Point translated to Rich Text Format Power Point translated to Hyper Text Lecture 3 posted 10/8/01: Power Point Power Point translated to Rich Text Format Power Point to Hyper Text Lecture 4 posted 10/12/01: Game Playing Latex source Latex translated to Hyper Text PS PDF Lecture 6A posted 10/12/01: Power Point Power Point translated to Rich Text Format Power Point translated to Hyper Text Lecture 6B posted 10/12/01: Game Playing Latex Source Latex translated to Hyper Text PS PDF Lecture 7 posted 10/15/01: Power Point Power Point translated to Rich Text Format Power Point translated to Hyper Text Lecture 8 posted 10/18/01: Power Point Power Point translated to Rich Text Format Power Point translated to Hyper Text Movies from this lecture: AVI Animation 1 AVI Animation 2 AVI Animation 3 AVI Animation 4 AVI Animation 5 AVI Animation 6 Lecture 9/10 posted 10/24/01: Local Search Latex Source Latex translated to Hyper Text PS PDF Lecture 11/12 posted 10/29/01: Knowledge Representation Power Point Power Point translated to Rich Text Format Power Point translated to Hyper Text Lecture 13/14 posted 11/02/01: First Order Logic Power Point Power Point translated to Rich Text Format Power Point translated to Hyper Text Lecture 18 posted 11/09/01: Ontologies Power Point Power Point translated to Rich Text Format Power Point translated to Hyper Text Lecture 19 posted 11/14/01: Planning Power Point Power Point translated to Rich Text Format Power Point translated to Hyper Text Lecture 21 posted 11/19/01: Planning Continued Power Point Power Point translated to Rich Text Format Power Point translated to Hyper Text Lecture 22 posted 11/21/01: Probability Latex Source Latex translated to Hyper Text PDF Lecture 23 posted 11/27/01: Bayes Nets Latex Source Latex translated to Hyper Text PDF Lecture 24 posted 11/27/01: Bayes Nets Continued Latex Source Latex translated to Hyper Text PDF Lecture 24B posted 12/03/01: Gibbs Sampling Power Point Power Point translated to Rich Text Format Power Point translated to Hyper Text Lecture 25 posted 12/06/01: Intro to learning Power Point Power Point translated to Rich Text Format Power Point translated to Hyper Text Lecture 26 posted 12/6/01: Bayesian Learning Latex Source Latex translated to Hyper Text PDF Lecture 27 posted 12/3/01: Decision Trees Mitchell's original Latex Source Latex translated to Hyper Text Postscript Lecture 28 posted 12/3/01: Neural Nets Mitchell's original Latex source Latex translated to Hyper Text Postscript Lecture 28B posted 12/10/01: Hebbian Learning Power Point Power Point translated to Rich Text Format Power Point translated to Hyper Text Lecture 29 posted 12/6/01: Support Vector Machines No good text based source yet -djp3 PDF: Support Vector Machine Slides Readings: Reading Due Date R&N ch 5 10/12 ch 3.7, also ch 6 and 7 10/18 Practice Mid-Term Questions MS Word RTF Stephen A. Cook and David G. Mitchell, "Finding Hard Instances of the Satisfiability Problem: A Survey", in Dingzhu Du, Jun Gu, and Panos M. Pardalos, editors, The Satisfiability Problem: Theory and Application, volume 35 of DIMACS Series in Discrete Mathematics and Theoretical Computer Science, pages 1-17. American Mathematical Society, 1997. Excellent overview of both the phase transition phenomena and the GSAT/Walksat local search algorithms. PS PS: Support Vector Machine Tutorial Assignments: Homework 1 posted 10/8/01 due 10/12/01: PS , PDF Homework 2A posted 10/12/01 due 10/19/01: PS , PDF , HTML Additional resources: Here is a Perl script that will do some very basic tests your tic-tac-toe implementation. ttt-server.pl Here is a Perl script that will play a very bad game of tic-tac-toe. ttt.pl A good exercise would be to run the following 'ttt-server.pl ttt.pl ttt.pl 2' . This command line will tell the tic-tac-toe server program to run 2 games between the program ttt.pl and the program ttt.pl Homework 2BC posted 10/19/01 due 10/26/01 and 11/5/01 10:00am: PS , PDF , HTML Homework 3A posted 11/5/01 due 11/14/01: Word , HTML Solution Set Homework 3B posted 11/15/01 due 11/23/01: Word , OpenOffice , Postscript , Acrobat PDF , Text , Html Download the binary here: Linux Tarball/bzip2 I liked Rick's solution because it only had a move and a push predicate. This requires more work in general because you have to specify more facts, but Rick made a script to transform an ASCII representation into a PDDL file which eliminated the pain and increased the elegance. Rick Cox's solution Sangyun had a similar solution that was also nice. Sokoban Domain file, Sokoban Problem 3 file Homework 4a posted 11/28/01 due 12/13/01: PDF Solution Set Homework 4b posted 11/28/01 due 12/17/01: TEXT Resources: A program to discretize a data set. discretize.pl C4.5: c4.5 Programs to perform cross-validation. cv.pl which uses ca.pl and driver (sample) and Datasets(provided by Nick Deibel) updated 09:38 12/10/01: Click Here   Schedule: Schedule of Topics date  session  topics  notes  M Oct 1 #1 1 introduction to AI (R&N Ch 1) intro  W Oct 3 #2 1 introduction to AI continued (R&N Ch 1) F Oct 5 #3 2 uniformed search (R&N Ch 3) hm1 out M Oct 8 #4 3 A* search (R&N 4.1-3) W Oct 10 #5 Game tree search (R&N ch 5) F Oct 12 #6 Game tree search continued (R&N ch 5) hm1 due, hm2 out M Oct 15 #7 Constraint satisfaction (R&N 3.7) W Oct 17 #8 Constraint satisfaction (Lecture slides) F Oct 19 #9 Local Search (R&N 4.4 and Lecture Slides) (tic-tac-toe due) M Oct 22 #10 Local Search continued (Lecture Slides and R&N 20.8) W Oct 24 #11 Knowledge Representation:  Propositional Logic (R&N Ch 6) F Oct 26 #12 Knowledge Representation: Propositional Logic continued (R&N Ch 7.1-3, 9.6) (chess version 1 due) Midterm study guide out M Oct 29 #13 Diagnostic Reasoning (lecture slides)  W Oct 31 #14 Midterm Exam F Nov 2 #15 First-order Logic (R&N 7.1-2) M Nov 5 #16 First-order Logic (R&N page 270, sec 9.6) (chess final due), hm3 out W Nov 7 #17 CHESS COMPETITION - meet in Sieg 322 - Pizza F Nov 9 #18 Ontologies (R&N 7.3, 8.4 to page 234) M Nov 12  NO SCHOOL W Nov 14 #19 Ontologies wrapup hm3 part A due (please try!) F Nov 16 #20 Planning (R&N new handout 11.1, 11.4, 11.2, plus lecture slides) M Nov 19 #21 Planning cont. (R&N new handout 11.1, 11.4, 11.2, plus lecture slides) hm3 part B due W Nov 21 #22 Probabilistic reasoning and Bayes Nets (R&N Ch 14, Ch 15) F Nov 23 NO SCHOOL M Nov 26 #23 Probabilistic reasoning and Bayes Nets cont. (R&N Ch 14, Ch 15) W Nov 28 #24 Rule learning (R&N 18) hm4 out (last assignment!) F Nov 30 #25 Rule learning and Text Classification (R&N Ch 18 and 23.1) M Dec 3 #26 Learning in Neural and Belief Networks (R&N 19) T Dec 5 #27 Learning in Neural and Belief Networks (R&N 19) F Dec 7 #28 Markov Decision Processes (R&N 17.1-3) M Dec 10 #29 Guest lecture: Adaptive Systems - Eric Horvitz (MSR) W Dec 12 #30 What Does it All Mean? (R&N 26,27) LAST DAY OF CLASS M Dec 15 hm 4 due W Dec 19  FINAL EXAM - 8:30 a.m. - MGH 254 - Open book and notes!

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