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":

• submit a one-page outline of the paper you intend to write to the instructor
• hand in the paper itself, which will be sent out to other students for peer review
• perform peer review of papers from other students in the class

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:

• Y. Shoham and K. Leyton-Brown, Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations, Cambridge University Press, 2009.

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:

• N. Nisan, T. Roughgarden, E. Tardos, and V. Vazirani (Eds.), Algorithmic Game Theory, Cambridge University Press, 2007.

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

• D. Fudenberg and Tirole, Game Theory, MIT Press, 1991;
• M. Osborne and A. Rubinstein, A Course in Game Theory, MIT Press, 1994.

Good coverage of linear programming is given by:

• J. Nocedal and S. Wright, Numerical Optimization, Springer, 1984.

A good book about auction theory is:

• V. Krishna, Auction Theory, Elsevier, 2002.

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

• Final Take-Home Exam: download the PDF here (updated). You have 48 50 hours, Tuesday, December 6, 9 PM PST to Thursday, December 8, 9 PM 11 PM PST. Please submit the exam by email to Dave Thompson, at dav...@cs.ubc.ca. Late exams will be penalized at 10% of the total grades per late hour. (So don't be late!) You must sign an honor code statement indicating that you referred to no resources beyond your own notes, the textbook Multiagent Systems: Algorithmic, Game-Theoretic, and Logical Foundations, lecture slides, and assignments/solutions to assignments. In particular, you may not refer to any other resources, including web sites, books, and people. You must work alone, and cannot consult with other students from the class. If your final grade is above 80% (uncurved), you will be given the option of counting the final at 30% and the midterm at 10%. In this case, the more favourable option will automatically be applied on your behalf.
• Projects:
  • 1,13
  • 2,3
  • 4
  • 5,7
  • 6
  • 8 (missing; you don't need to review this one)
  • 9
  • 10
  • 11
  • 12
  • 14
• Project Reviews Due: Dec 30, 11:59 PM, any time zone you choose. Submit them using this online form. You'll be graded only on the level of detail and insight in your comments, not on whether or not your assessment agrees with the instructor's.

Last updated December 23, 2011