Readings other than the textbooks that do not appear with hyperlinks below can be found in by clicking Reserves on the left menu bar in Blackboard.
date  classwork  assignments 

Thur Sept 2  1. Introduction to the course  1. Read B&L Chapter 1. Respond:  What is knowledge?  What is representation?  What is reasoning? Due by 10pm Monday Sept 6. 
Tues Sept 7  2. Knowledge representation and reasoning B&L Ch 1 
2. Read B&L Ch 2.12.4. Respond: 3. Read B&L Ch 2.5. Respond: 
Thur Sept 9  class cancelled  
Tues Sept 14  3. The language of firstorder logic B&L Ch 2 

Thur Sept 16  4. The language of firstorder logic, continued 
Read B&L Ch 3. Freeform response. Exercise Set 1: Interpretations & Models 
Tues Sept 21 
B&L Ch 3 
4. Read B&L Ch 4. Respond: 
Thur Sept 23  class cancelled  
Tues Sept 28  6. Resolution B&L Ch 5 

Thurs Sept 30  7. Resolution, continued 
Exercise Set 2: Resolution Proofs 5. Reading: B&L Ch 4 Exercises 5 and 6 (don't solve them, just read them); also Section 2.3 of the paper by Gomes et al., Satisfiability Solvers, 2008 (See course reserves). 
Tues Oct 5  8. Resolution, continued


Thur Oct 7  9. Resolution, continued 
Programming Assignment 1: Build a SAT Solver Due by turnin by 11:59pm Tuesday Oct 26 
Tues Oct 12  10. Basic satisfiability algorithms B&L Ch 5 exercises 5 and 6 Section 2.3 of C. P. Gomes, H. Kautz, A. Sabharwal, & B. Selman, Satisfiability Solvers, in F. van Harmelen, V. Lifschitz, & B. Porter, Eds., Handbook of Knowledge Representation, in the series Foundations of Artificial Intelligence, Vol. 3, Elsevier, 2008. (See course reserves) 
Read the section in R&N on "Planning with Propositional Logic" (2nd Edition, Sec. 11.5; 3rd Edition, Sec. 10.4.1). Write a short (one paragraph) response summarizing the basic idea of how planning problems can be turned into SAT. Due by 10pm Wednesday Oct 13. The Subject: line of your response should be exactly the following: Subject: Reading Oct 13 SATPLAN 
Thur Oct 14  11. Planning as satisfiability A. Blum and M. Furst, Fast Planning Through Planning Graph Analysis, Artificial Intelligence, 90:281300 (1997). Henry Kautz and Bart Selman, Pushing the Envelope: Planning, Propositional Logic, and Stochastic Search, Proc. AAAI96. 

Tues Oct 19  12. Modern satisfiability algorithms C. P. Gomes, H. Kautz, A. Sabharwal, & B. Selman, Satisfiability Solvers, in F. van Harmelen, V. Lifschitz, & B. Porter, Eds., Handbook of Knowledge Representation, in the series Foundations of Artificial Intelligence, Vol. 3, Elsevier, 2008. (See course reserves) 
Read the section B&L Chapters 5 and 6. Respond to the questions:  Complete the sentence: "In SLD resolution, the leaf at the top of the tree is aways the _________, and the leafs along the left side of the tree are ___________."  For the propositional case, why is forwardchaining more efficient than backward chaining for reasoning with Horn clauses?  Why does the book call PROLOG an example of "procedural control of reasoning"? Due by 10pm Monday Oct 25. The Subject: line of your response should be exactly the following: Subject: Reading Oct 25 PROLOG 
Thur Oct 21  Midterm exam  
Tues Oct 26  13. Horn Clauses B&L Ch 5 

Thur Oct 28  14. Prolog B&L Ch 6 
Reading: B&L Ch 11, Sections 11.1, 11.2.111.2.4, and 11.4. Respond: 
Tues Nov 2  15. More Prolog 

Thur Nov 4 
B&L Ch 11 
Programming Assignment 2: Problem Solving in Prolog Reading: B&L Ch 13. Respond: 
Tues Nov 9 
B&L Ch 13 
Homework: Problem 3, pg 283 in B&L. Due Nov 16 in class. 
Thur Nov 11 
C. Barrett, R. Sebastiani, S. A. Seshia, & C. Tinelli, Satisfiability Modulo Theories, in A. Biere, H. van Maaren, M. Heule and Toby Walsh, Eds., Handbook of Satisfiability, IOS Press, 2009.(See course reserves) 
Homework (due Nov 18 in class) 
Tues Nov 16  19. Reasoning about the knowledge of multiple agents J. Halpern, Reasoning about knowledge: a survey, in D. Gabbay, C. J. Hogger, and J. A. Robinson, Eds.,Handbook of Logic in Artificial Intelligence and Logic Programming, Vol. 4, Oxford University Press, 1995. 
Homework (due Nov 23 in class) 
Thur Nov 18  20. Limited and approximate inference Liu, Y., Lakemeyer, G., and Levesque, H., A logic of limited belief for reasoning with disjunctive information, Proc. of the KR2004 Conference, Whistler, BC, 2004. H. Kautz and B. Selman, A General Framework for Knowledge Compilation, Proceedings of the First World Conference on the. Fundamentals of Artificial Intelligence, Paris, 1991. 
Homework  due Nov 30 in class 
Tues Nov 23 
B&L 12.112.4; R&N 14.5 
Homework: Problem 4 in section 12.6 (pg 265) of the B&L textbook with the following changes: do only parts a, b, d(iiii). Due Nov 30 in class. 
Thur Nov 25  Thanksgiving break  
Tues Nov 30  22. Bayesian reasoning using MAXSAT and modelcounting J. D. Park, Using Weighted MAXSAT Engines to Solve MPE, Proceedings of the Eighteenth National Conference on Artificial Intelligence (AAAI02), Edmonton, Alberta, 2002, pages 682687. T. Sang, P. Beame, & H. Kautz., Solving Bayesian Networks by Weighted Model Counting, Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI05), Pittsburgh, PA, 2005. 
Homework  due in class Dec 7 
Thur Dec 2  23. Markov logic P. Domingos & D. Lowd, Markov Logic: An Interface Layer for Artificial Intelligence, Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool, 2009. (See course reserves) 
Homework  due in class Dec 9 
Tues Dec 7  24. Markov logic, continued (additional slides) 

Thur Dec 9  25. Review of course since midterm and limits of logic pdf version of slides 

Mon Dec 20  Takehome final exam. Available for download from this page on Monday Dec 13. Due by turnin by 11:59pm on Monday Dec 20. The exam will be designed to be completed in approximately 3 hours. 
Back to course home