CPSC 532L - Foundations of Multiagent Systems
(Term 1, Session 101, 2011-12)

Overview Grades Final Project Text Schedule Handouts


 

Overview

Course Description:  This course examines the mathematical and computational foundations of modern multiagent systems, with a focus on game theoretic analysis of systems in which agents cannot be guaranteed to behave cooperatively.  The course emphasizes student participation, featuring seminar-style discussion as well as traditional lectures. The course will culminate in a small research project in which students survey existing literature and possibly explore open research questions.

 

      Term: 1

      Meeting Times: Monday, Wednesday, 3:30 - 5:00 PM

      First Class: Wednesday, September 7, 2011

      Location: ICCS 206

      Instructor: Kevin Leyton-Brown

      Instructor's Office Location: CICSR 185

      Office Hours: Monday, Wednesday, 5:00 - 5:30 PM, or by appointment

Course Topics: Overall, problems at the interface of economic theory and computer science.  (No prior experience in economics is assumed.) Specific topic include: Games: normal-form; extensive-form; repeated; stochastic; Bayesian.  Computation of game-theoretic solution concepts. Mechanism design: key positive and negative results.  Single-good auctions. Combinatorial auctions: bidding; mechanisms; computational issues.

 

Prerequisites:  There are no formal prerequisites, and it is assumed that most students in the class will be unfamiliar with game theory, mechanism design, auction theory, and the literature on multiagent systems. Since some of the material to be covered is quite formal mathematically, students do need to be able to construct and follow formal proofs.  Relevant mathematical/CS background includes introductory knowledge of probability theory, computational complexity and combinatorial optimization. Much of the work associated with the course will revolve around reading papers from the Multiagent Systems literature, writing a survey or research paper, and presenting findings to the class. As a result, students who have trouble reading, speaking or writing comfortably in English will find themselves at a disadvantage.

 

Academic Honesty: Plagiarism is a serious offence and will be dealt with harshly.  I consider plagiarism to be the unattributed use of an external source (e.g., another student, a web site, a book) in work for which a student takes credit, or the inappropriate use of an external source whether or not attribution is made. The seriousness of the offence depends on the extent to which the student relied upon the external source.  Assignments and midterms will include an "honour code" statement which you will be required to sign, specifying forms of collaboration and reference to non-course materials that are acceptable. For projects, you must cite all external sources that you use, and the vast majority of the project must be written in your own words. Any text that you take verbatim from another source must be in quotation marks and followed by a citation.


Grades

Overall Grading Scheme
Warning: I reserve the right to make changes to the exact percentage breakdowns shown here.  However, the following grading scheme should be approximately accurate, and indicates the components of the class upon which you will be graded.


Assignments (three or four) 20 %
Test 1 (in-class) 20 %
Test 2 (take-home) 20 %
Project outline 7 %
Project writeup 20 %  (10% instructor; 10% peer)
+ up to 2 bonus marks
Peer Review of Other Students' Final Project Papers 3 %
Participation in Discussions; Attendance 10 %

 

Curving Grades and Peer Review: Final grades will be curved to give the overall distribution of grades a desired mean and standard deviation. Bonus marks will be applied after grades are curved.  Peer review is an important component of the class, and will be taken into account when evaluating papers.  Since this is a Multiagent Systems course, a grading scheme has been constructed that does not provide students with any ability to influence their own grades by reviewing other students strategically.  The curve for a given student x will be calculated disregarding x's presentation and paper reviews of other students.

 

Assignments:  The course will include three or four assignments.  Dates on which assignments will become available and due dates are given in the schedule below; assignments are always due at the beginning of class.  Assignments will probably not be weighted equally: weighting will be proportional to the total number of available points.  In particular, the last assignment may be weighted substantially more heavily since it will cover material not reviewed on the midterm exam. Students will be given three late days for use on the assignments.  These are intended to help avoid scheduling conflicts with other courses, personal commitments, and emergencies.  Therefore, no additional late days will be granted except under truly exceptional circumstances.  Late assignments will be penalized at 20% per day.


Final Project

CPSC 532L will culminate with a final project that allows students to explore material that was not covered in class and to share that material with other students.  The project involves students writing a paper on a topic of interest within Multiagent Systems, and then reading and evaluating each other's papers.  Here is the "pipeline":

The topic of the final project need not be too ambitious; it's fine to perform a survey of a subarea in Multiagent Systems or a compare-and-contrast study of two or more influential papers.  (Note, however, that even if you perform a survey, your project must be written entirely in your own words, and must do more than simply reiterate content from the papers you survey.) If you plan to do more work in the area, you can also use the project to develop your own research ideas.  In future weeks a list of possible topics will appear in this space.  Please note that assignment late days cannot be applied to the final project.

 

Your project should be written using the LaTeX document preparation system, which is the standard for writing research papers in computer science. Please use the "article" class file with default margins, 10 pt font; in this style, your project should be between 6-10 pages, not including your bibliography.


Texts

We will be using the following textbook:

Another good general text for exploring more advanced material in the research area, written largely from a CS theory perspective, is the following edited volume:

If you'd like to do additional reading on Game Theory, I recommend the following supplemental books:

Good coverage of linear programming is given by: A good book about auction theory is: A wide variety of texts covering multiagent systems, game theory and microeconomic theory have been purchased by the CS reading room.  They are available in a special section, under the heading "game theory reading group".  Just ask the librarian if you can't find them!


Schedule

Slides from each lecture may be accessed by clicking on the links under "lecture topic"; applicable section numbers from the textbook are also given. Slides will not necessarily be available in advance; however, last year's slides can be accessed from last year's course webpage. Assignment and project due dates will be added throughout the term. 

 

Date Lecture Topic  (textbook sections) Milestones
September 7 Introduction ( Introduction)  
September 12 Game Theory Intro ( 3.2)  
September 14 From Optimality to Equilibrium ( 3.2 - 3.3)  
September 19 Maxmin; Computing Maxmin ( 3.3 - 3.4.1, 4.1, 4.4, Appendix B)  
September 21 Domination; Computing Domination ( 3.4.3 - 3.4.4, 4.5) *  
September 26 Correlated Equilibrium; Computing CE ( 3.4.5, 4.6) Assignment 1
September 28 Behavioral Game Theory (this paper)  
October 3 Perfect-Information Extensive-Form Games ( 5.1)  
October 5 Imperfect Information Extensive-form Games ( 5.2) Assignment 1 due
October 10 Thanksgiving Holiday: no class  
October 12 Repeated Games; The Folk Theorem ( 6.1, 6.2) Assignment 2
October 17 Stochastic Games; Bayesian games ( 6.2, 6.3)
October 19 Social choice ( 9.1 - 9.3)  
October 24 Arrow's Impossibility Theorem ( 9.4) Assignment 2 due
October 26 Mechanism Design Intro ( 9.5 - 10.1)  
October 31 Midterm Exam *  
November 2 Revelation Principle; Quasilinear Utility ( 10.2 - 10.3.1)  
November 7 Quasilinear Mechanism Design ( 10.3.2 - 10.4.1) Project outline due
November 9 The VCG Mechanism ( 10.4.2 - 10.4.4) Assignment 3
November 14 Advanced Mechanism Design ( 10.4.5 - 10.7) *
November 16 Single-Good Auctions ( 11.1 - 11.1.3) * Assignment 4
November 21 Revenue Equivalence ( 11.1.4 - 11.5) * Assignment 3 Due
November 23 Advanced Single-Good Auctions ( 11.1.6 - 11.1.10)  
November 28 Multiunit Auctions ( 11.2)  
November 30 Combinatorial Auctions ( 11.3) Assignment 4 Due