Index

Lecture series are sponsored by

Fall 2011 program

Oct. 19, 2011 Repeated Games Tutorial
Ichiro Obara (Associate Professor at UCLA)

Nov. 2, 2011 Ostracism
David Miller (Assistant Professor at UCSD)

Nov. 9, 2011 Mean Field Equilibria of Dynamic Auctions with Learning
Ramesh Johari (Associate Professor at Stanford)

Nov. 30, 2011 Dynamic Games Tutorial
Paulo Tabuada (Associate Professor at UCLA)

Winter 2012 program

Jan. 11, 2012 Distributed and Sequential Decision Making
Vikram Krishnamurthy (Professor at UBC)

Feb. 8, 2012 Optimization in Presence of Random Constraints
Angelia Nedich (Assitant Professor at UIUC)

Feb. 22, 2012 Learning and information exploitation in networked scenarios
Jorge Cortes (Associate Professor at UCSD)

Feb. 29, 2012 Mean field stochastic games
Tembine Hamidou (Assistant Professor at Supelec, France)

Mar. 7, 2012 Game Design for Distributed Optimization
Jason Marden (Assistant Professor at University of Colorado at Boulder)

Spring 2012 program

April. 4, 2012 Mechanism Design
Moritz Meyer-ter-Vehn (Assistant Professor at UCLA)

April. 11, 2012 Robust Mechanism Design
Moritz Meyer-ter-Vehn (Assistant Professor at UCLA)

April. 18, 2012 Pricing and Efficiency in the Market for IP Addresses
Michael Schwarz (Principal Research Scientist at Yahoo! Research in Berkeley)

April. 25, 2012 Game Theory for Security: Algorithms, Deployed systems, Lessons learned
Milind Tambe (Professor at USC)

May. 9, 2012 Economics and Machine Learning
Preston McAfee (Vice President and Research Fellow Yahoo! Research)

May. 16, 2012 Computing Game-Theoretic Solutions for Security
Vincent Conitzer (Professor at Duke)

May. 23, 2012 Adaptive Networks (part 1)
Ali Sayed (Professor at UCLA)

June. 6, 2012 Adaptive Networks (part 2)
Ali Sayed (Professor at UCLA)

May 9 Lecture: Dr. Preston McAfee

Internet advertising exchanges possess three characteristics—fast delivery, low values, and automated systems—that influence market design. Automated learning systems induce the winner’s curse when several pricing types compete. Bidders frequently compete with different data, which induces randomization in equilibrium. Machine learning causes the value of information to leak across participants. Discrimination may be used to induce efficient exploration, although publishers (websites) may balk at participating. The creation of “learning accounts,” which divorce payments from receipts, may be used to internalize learning externalities. Under some learning mechanisms the learning account eventually shows a surplus. The solution is illustrated computationally.

Bio:
Dr. Preston McAfee is a Vice President and Research Fellow at Yahoo! Research where he leads the Microeconomics and Social Systems group. Prior to Yahoo!, he was the J. Stanley Johnson Professor of Business, Economics, and Management at the California Institute of Technology, where he was the executive officer for the social sciences. He taught business strategy, managerial economics, and introductory microeconomics.

May 16 Lecture: Prof. Vincent Conitzer

Algorithms for computing game-theoretic solutions are now deployed in real-world security domains, such as air travel. These applications raise some hard questions. How do we deal with the equilibrium selection problem? How is the temporal and informational structure of the game best modeled? What assumptions can we reasonably make about the utility functions of the attacker and the defender? And, last but not least, can we make all these modeling decisions in a way that allows us to scale to realistic instances? I will present our ongoing work on answering these questions. This talk is related to Milind Tambe's April 25 talk in the same seminar series. I will try to avoid overlap, but it is not necessary to have seen Milind's talk. Compared to that talk, this talk will focus less on applications and more on basic underlying game-theoretic and algorithmic insights.

Bio:
Vincent Conitzer is the Sally Dalton Robinson Professor of Computer Science and Professor of Economics at Duke University. He received Ph.D. (2006) and M.S. (2003) degrees in Computer Science from Carnegie Mellon University, and an A.B. (2001) degree in Applied Mathematics from Harvard University. His research focuses on computational aspects of microeconomics, in particular game theory, mechanism design, voting/social choice, and auctions. This work uses techniques from, and includes applications to, artificial intelligence and multiagent systems. Conitzer has received the IJCAI Computers and Thought Award, recognition as one of "AI's Ten to Watch" by IEEE Intelligent Systems, an NSF CAREER award, a Sloan fellowship, the inaugural Victor Lesser dissertation award, an honorable mention for the ACM dissertation award, and several awards for papers and service at the AAAI and AAMAS conferences. Conitzer and Preston McAfee are the founding Editors-in-Chief of the ACM Transactions on Economics and Computation (TEAC).