Previous Speakers 2008-2009

Ninth lecture:
Empirical Game Analysis and the Behavior of Software Agents
Michael Wellman, University of Michigan
Professor, Computer Science and Engineering
Date: May 27th, 2009
Time: 1:00pm - 2:30pm
Location: Calit2 Auditorium, Atkinson Hall, UC San Diego


Click here for abstract and bio

Abstract:

The games agents play -- in markets, conflicts, or most other contexts -- often defy strict game-theoretic analysis. Games may be unmanageably large (combinatorial or infinite state or action spaces), and present severely imperfect information, which could be further complicated by partial dynamic revelation. Moreover, the game may be specified procedurally, for instance by a simulator, rather than in an explicit game form.

With colleagues and students over the past few years, I have been developing a body of techniques for strategic analysis, adopting the game-theoretic framework but employing it in domains where direct "model-and-solve" cannot apply. This empirical game-theoretic methodology embraces simulation, approximation, statistics and learning, and search. Through applications to canonical auction games, and rich trading scenarios, we demonstrate the value of empirical methods for extending the scope of game-theoretic analysis. This perspective also sheds insight into behavioral models and bases for predicting joint action in complex multiagent scenarios.

Bio:

Professor Michael Wellman received a PhD from the Massachusetts Institute of Technology in 1988 for his work in qualitative probabilistic reasoning and decision-theoretic planning. From 1988 to 1992, Wellman conducted research in these areas at the USAF's Wright Laboratory. For the past 15+ years, his research has focused on computational market mechanisms for distributed decision making and electronic commerce. As Chief Market Technologist for TradingDynamics, Inc. (now part of Ariba), he designed configurable auction technology for dynamic business-to-business commerce. Wellman previously served as Chair of the ACM Special Interest Group on Electronic Commerce (SIGecom), and as Executive Editor of the Journal of Artificial Intelligence Research. He is a Fellow of the Association for the Advancement of Artificial Intelligence and the Association for Computing Machinery. He is a member of the university's Artificial Intelligence Laboratory, and is a professor and associate chair of the Department of Computer Science and Engineering at the University of Michigan-Ann Arbor.

 

Eighth lecture:
Piercing the Veil of Ignorance
Shachar Kariv, UC Berkeley Professor of Economics
Date: April 29th, 2009
Time: 10:30am-Noon
Location: Calit2 Auditorium, Atkinson Hall, UC San Diego


Click here for abstract and bio

Abstract:

The talk is motivated in part by work of John Rawls and John Harsanyi, who argue for ethical theories based on social choices that individuals would make in the original position, behind a veil of ignorance -- that is, "without knowing their own social and economic positions, their own special interests in the society, or even their own personal talents and abilities (or their lack of them)." The PI's points of departure from the work of Rawls and Harsanyi -- and the enormous literature they spawned -- comes from two observations that have been quite overlooked. The first is that (under natural assumptions), choice behavior/preferences behind the veil of ignorance are determined by choice behavior/preferences in front of the veil of ignorance. The second is that although the original position is a hypothetical situation developed as a thought experiment, it is possible to "replicate" it in the laboratory. Beginning with the theoretical and experimental findings, we can address important questions concerning personal and social preferences, including: Is observed behavior consistent with the utility maximization hypothesis on which economic theory relies? Can underlying preferences be recovered from observed choices? Can social preferences be characterized experimentally? How do preferences differ across subjects? What is the relationship between personal preferences and social preferences? A related paper (with Bill Zane of UCLA) can be downloaded from http://emlab.berkeley.edu/~kariv/KZ_I.pdf.

Bio:

Shachar Kariv was educated at Tel-Aviv University and New York University, where he received his PhD in 2003, the same year he joined Berkeley's economics department. Professor Kariv was a visiting member of the Institute for Advanced Studies School of Social Science (2005-6). He is the recipient of the UC Berkeley Graduate Economics Association Outstanding Advising Award (2006-7) and of New York University Outstanding Teaching Awards (2001, 2002) and the Outstanding Dissertation Award in the Social Sciences (2003). He has also received a National Science Foundation Grant for studying decisions under uncertainty (2006-7). Professor Kariv's research has been published in a variety of academic journals including, the American Economic Review, Games and Economic Behavior, and Economic Theory.

 

Seventh lecture:
Would You Be Happier If You Were Richer? and Other Puzzles on the Road to Measuring National Well-Being
David Schkade
Professor of Economics, Rady School of Management
Date: April 10th, 2009
Time: 1:00pm - 2:30pm
Location: Calit2 Auditorium, Atkinson Hall, UC San Diego


Click here for abstract and bio

Abstract:

The belief that high income is associated with good mood is widespread but mostly illusory. People with above-average income are relatively satisfied with their lives but are barely happier than others in moment-to-moment experience, tend to be more tense, and do not spend more time in particularly enjoyable activities. Moreover, the effect of income on life satisfaction seems to be transient. We argue that people exaggerate the contribution of income to happiness because they focus, in part, on conventional achievements when evaluating their life or the lives of others.

If there is more to life than money, how can this component be measured and incorporated into policy making? The Day Reconstruction Method (DRM) assesses how people spend their time and how they experience the various activities and settings of their lives, combining features of time-budget measurement and experience sampling. Participants systematically reconstruct their activities and experiences of the preceding day with procedures designed to reduce recall biases. Results from samples in the US, France and Denmark are used to illustrate the utility of evaluated time use. A variant of the DRM that is adapted for use with large, nationally representative surveys is developed, and employed to propose a new approach for measuring features of society's subjective well-being, based on evaluated time use, which we call National Time Accounting.

Bio:

The primary focus of Professor Schkade’s research is on the psychology of judgment and decision making, and how decision making can be improved. His scholarly work includes over 60 published papers and two books, including his most recent, "Are Judges Political? An Empirical Analysis of the Federal Judiciary." He has studied several public policy issues, including how jurors make punitive damage decisions, the effect of ideology on the decisions of federal appellate judges, environmental resource valuation, valuation of health effects for cost-benefit analysis and why people choose to become organ donors.

He has also served on committees of the National Academy of Sciences, most recently on organ donation, and on cost-effectiveness of federal health-related policies, programs and regulations.

His work has been supported by grants from the National Science Foundation, the Environmental Protection Agency, the Hewlett Foundation, the National Institutes of Health, the Electric Power Research Institute, Exxon and IBM. He teaches negotiation, decision analysis, organizational behavior, managerial decision making, statistics, and research methods. He serves or has served on the editorial boards of several major journals, and on review panels of the National Science Foundation and the Environmental Protection Agency.

He won both the top research and MBA teaching awards at the McCombs School of Business at the University of Texas, and was selected to Who’s Who in Economics 1990-2000. His research on punitive damages has been cited in numerous court cases, including opinions by the U.S. Supreme Court, U.S. Circuit Courts of Appeals and the California State Supreme Court. His editorials, quotations and references to his work have appeared in numerous media outlets, among them the New York Times, Wall Street Journal, Washington Post, Financial Times, LA Times, Dallas Morning News, Time Magazine, CNN, UPI, Reuters, ABC, CBS, NBC, NPR, and BBC.

 

Sixth lecture:
Behavioral Welfare Economics
B. Douglas Bernheim
Lewis and Virginia Eaton Professor in Economics
Stanford University
Date: March 18, 2009
Time: 1:00pm - 2:30pm
Location: Calit2 Auditorium, Atkinson Hall, UC San Diego


Click here for abstract and bio

Abstract:

This paper critically assesses several competing proposals for general normative frameworks that would encompass non-standard models of choice. Most existing proposals equate welfare with well-being. Some assume that well-being flows from the achievement of well-defi ned objectives, and that those objectives also guide choices; the trick is to formulate a framework in which less-than-completely coherent choice patterns reveal the unobserved objectives. Others are predicated on the contention that well-being, and hence welfare, is directly measurable. Both of those approaches encounter serious conceptual diffi culties. An alternative approach, developed by Bernheim and Rangel [2009], defi nes welfare directly in terms of choice. It entails a generalized welfare criterion that respects choice directly, without requiring any rationalization involving potentially unverifi able assumptions concerning underlying objectives and their relationships to choice. Because useful behavioral theories generally envision a substantial degree of underlying coherence in behavior, that criterion leads to a rich and tractable normative framework.

Bio:

Professor Bernheim is the Lewis and Virginia Eaton Professor in Economics. His teaching interests include public fi nance, industrial organization, and microeconomic theory. His current research includes behavioral welfare economics; models of decision making with cognitive limitations, with applications to addiction, saving, marketing, and other behavior; the theory of cheating within imperfect cartels; collective decision-making in majoritarian institutions. Dr. Bernheim is a Senior Fellow in the Stanford Institute for Economic Policy Research, and is Co-director of its Finance Program.

Prof. Bernheim's Web site: http://www.stanford.edu/~bernheim/
Paper: "Neuroeconomics: A Sober (but Hopeful) Appraisal", AEJ: Microeconomics (forthcoming) http://www.nber.org/papers/w13954.pdf

 

Fifth lecture:
Robust Mechanism Design: A Survey of Recent Work
Dirk Bergemann, Yale University
Professor of Economics
Date: February 20, 2009
Time: 2:00pm - 3:30pm
Location: Calit2 Auditorium, Atkinson Hall, UC San Diego


Click here for abstract and bio

Bio:
Dirk Bergemann is the Douglass and Marian Campbell Professor of Complex Systems, Political Science and Economics, at Yale University. His most recent work is on robust mechanism design and dynamic allocation mechanisms. He has also worked on games with Bayesian learning and financial contracts. Bergemann earned a B.A. in economics and sociology at J.W. Goethe University in Frankfurt and a M.A. and Ph.D. in economics from the University of Pennsylvania. He came to Yale in 1995 as an assistant professor and has been affiliated with the Cowles Foundation for Research in Economics at Yale since 1996. Dirk Bergemann has received several grants from the National Science Foundation to support his research and also has been awarded fellowships from the Alfred P. Sloan Research Fellowship and the German National Science Foundation. Bergemann is foreign editor for the Review of Economic Studies, and associate editor of several publications, among them Econometrica, Journal of Economic Theory and Games and Economic Behavior.

Abstract:

The theory of mechanism design helps us understand institutions ranging from simple trading rules to political constitutions. We can understand institutions as the solution to a well defined planner's problem of achieving some objective or maximizing some utility function subject to incentive constraints.

A common criticism of mechanism design theory is that the optimal mechanisms solving the well defined planner's problem seem too sensitive to the assumed structure of the environment. We suggest a robust formulation of the mechanism design and implementation problem. The talk will be based on past and current work by the authors.

Papers:
http://cowles.econ.yale.edu/P/cd/d15b/d1561-rr.pdf http://www.econ.yale.edu/~dirkb/pub/robust-mechanism.pdf


Fourth lecture:

Unpacking the Wisdom of Crowds
Scott E. Page, University of Michigan
Date: January 23, 2009
Time: 1:00pm - 2:30pm
Location: Room 1202, Computer Science and Engineering Building, UC San Diego


Click here for abstract and bio

Bio:
Scott Page is the Leonid Hurwicz Collegiate Professor of Complex Systems, Political Science, and Economics at the University of Michigan-Ann Arbor, and on the External Faculty of the Santa Fe Institute. He was an undergrad at Michigan, majored in math, and later taught math at the University of Wisconsin-Madison. Later he taught statistics and decision theory at Kellogg Graduate School of Management, then at Caltech (including his half serious talks on the economic impact of the Tournament of Roses). Prior to joining the University of Michigan-Ann Arbor, Page taught game theory courses at the University of Iowa. He is based in the Santa Fe Institute.

Abstract:
In this talk, Dr. Page will present three models for explaining the wisdom of crowds phenomenon, in which collections make better predictions than the individuals that comprise them. The first two models will be traditional models based on error cancellation and averaging. The third will be based on aggregating diverse predictive models using a framework developed by Hong and Page (2008). This talk is part of Calit2's 2008-2009 Behavioral, Social and Computer Sciences Seminar Series.

Website:
http://www.cscs.umich.edu/~spage/


Third lecture:

Strategic Network Formation with Structural Holes
Siddharth Suri, Yahoo! Research
Research Scientist

Date: December 11th, 2008
Time: 1:00 pm
Location: Calit2 Auditorium, Atkinson Hall,
UC San Diego


webcastArchived Webcast


Click here for abstract and bio

Bio:
Dr. Siddharth Suri joined the Human & Social Dynamics group at Yahoo! Research led by Duncan Watts in August 2008. Prior to that he was a postdoctoral associate working with Jon Kleinberg in the computer science department at Cornell University. Suri earned his Ph.D. in computer and information science from the University of Pennsylvania in January 2007 under the supervision of Michael Kearns. If you would like more information about his background, please see his CV.

Suri's research takes an interdisciplinary approach in studying the computational aspects of social networks as well as economic networks. Many modern technological networks such as the Internet, the World Wide Web, Facebook, and eBay involve social and/or economic interactions. Thus, he uses theories from sociology and models from economics in his study of algorithmic questions about these types of networks. For more information please see his research statement.

Abstract:
A fundamental principle in social network research is that individuals can benefit from serving as intermediaries between others who are not directly connected. Through such intermediation, they potentially can broker the flow of information and synthesize ideas arising in different parts of the network. These principles form the underpinning for the theory of structural holes, which studies the ways in which individuals, particularly in organizational settings, fill the "holes" between people or groups that are not otherwise interacting.

We apply a game-theoretic approach to this notion, studying the structures that evolve when individuals in a social network have incentives to form links that bridge otherwise disconnected parties. We model payoffs as a trade-off between the benefits of connecting non-neighboring nodes, and the cost, in effort, to maintain links - including settings where the costs are non-uniform to reflect the increased difficulty in spanning different parts of a hierarchical organization.

We find, both through theoretical results and computational experiments, that the equilibrium networks in this model have rich combinatorial structure, and capture qualitative observations arising in the study of structural holes. In particular, even in completely symmetric settings, individuals will differentiate themselves in equilibrium, occupying different social strata and receiving correspondingly different payoffs.

Selected Publications:
Strategic Network Formation with Structural Holes, J.Kleinberg, S. Suri, É. Tardos, and T. Wexler, EC 2008

An Experimental Study of the Coloring Problem on Human Subject Networks, M. Kearns, S. Suri, and N. Montfort, Science, 313(5788):824-827, 2006


Second Lecture:

A Model of Genetic Variation in Human Social Network
James Fowler, UC San Diego
Associate Professor, Political Science
Date: November 12, 2008
Time: 1:00 - 2:30 pm
Location: Calit2 Auditorium, Atkinson Hall, UCSD


Click here for abstract and bio

Bio:
James Fowler is an Associate Professor in the Political Science Department at the University of California, San Diego. His current interests include social networks, behavioral economics, evolutionary game theory, political participation, the evolution of cooperation, and genopolitics (the study of the genetic basis of political behavior). His CV is here.

In addition to his scientific research, James is currently working on a book for a general audience about social networks in everyday life (Connected! -- with Nicholas Christakis) that will be published by Little Brown (and more than a dozen other publishers worldwide), probably in early 2010.

James was recently named one of the Nifty Fifty "most inspiring" scientists by the San Diego Science Festival. Read their bio about him here.

Abstract:
Social networks influence the evolution of cooperation and they exhibit strikingly systematic patterns across a wide range of human contexts. Both of these facts suggest that variation in the topological attributes of human social networks might have a genetic basis. While genetic variation accounts for a significant portion of the variation in many complex social behaviors, the heritability of egocentric social network attributes is unknown. Here we show that three of these attributes (in-degree, transitivity, and centrality) are heritable. We then develop a "mirror network" method to test extant network models and show that none accounts for observed genetic variation in human social networks. We propose an alternative "attract and introduce" model that generates significant heritability as well as other important network features, and we show that this model with two simple forms of heterogeneity is well suited to the modeling of real social networks in humans. These results suggest that natural selection may have played a role in the evolution of social networks. They also suggest that modeling intrinsic variation in network attributes may be important for understanding the way genes affect human behaviors and the way these behaviors spread from person to person. More here.

 

Link to paper:
http://arxiv.org/ftp/arxiv/papers/0807/0807.3089.pdf

Speaker's website:
http://jhfowler.ucsd.edu/


First Lecture:

Nash Bargaining Via Flexible Budget Markets
Vijay Vazirani, Georgia Tech Professor
Date: Thursday, October 9, 2008
Time: 1:00 pm - 2:30pm
Location: Calit2 Auditorium, Atkinson Hall, UC San Diego


Click here for abstract and bio

Bio:
Dr. Vijay Vazirani is a professor in the School of Computer Science at Georgia Tech, and a member of the university's Information Security Center. He is the author of Approximation Algorithms, Springer-Verlag, Berlin, 2001. Vazirani earned his Ph.D. from UC Berkeley in 1983.

He is a leading researcher in algorithm design, and more generally, in the theory of computing. Throughout his research career, Vazirani has demonstrated a consistent ability to obtain novel algorithmic ideas, frequently of substantial mathematical depth, which while solving the problem at hand, also lay the groundwork for future contributions by others.

Vazirani's research career spans over twenty five years. During the first ten years, he made seminal contributions to the classical maximum matching problem which has historically played a central role in the development of the theory of algorithms. He discovered, jointly with other researchers, the fastest known sequential and parallel algorithms for his problem. Over the next ten years, Vazirani focused on approximation algorithms for NP-hard problems and had much influence on this area through work on several of its fundamental problems. In 2001, he published a book on this topic. He is currently working in algorithmic game theory, in particular on algorithms for computing market equilibria.

Abstract:
In his seminal 1950 paper, John Nash defined the bargaining game; the ensuing
theory of bargaining lies at the heart of game theory. In this work, we initiate
an algorithmic study of Nash bargaining games.

For a certain class of Nash bargaining games, we show that they can be transformed
into a market (in a new variant of a traditional market model from mathematical
economics). We then extend techniques developed in theoretical computer science over
the last seven years to give a combinatorial, polynomial time algorithm for
computing an equilibrium for this market. The latter in turn yields the solution to
the Nash bargaining game.

Over the years, a fascinating theory has started forming around a convex program
given by Eisenberg and Gale in 1959. Besides market equilibria, this theory touches
on such disparate themes as TCP congestion control and efficient solvability of
nonlinear programs by combinatorial means. Our work shows that the Nash bargaining
problem fits harmoniously in this collage of ideas.

For a general audience:
http://www-static.cc.gatech.edu/~vazirani/NB-Google.ppt

Live webcast:
http://calit2.net/webcast
[Windows Media and broadband connection required]

For the algorithmically inclined, there is more at http://www-static.cc.gatech.edu/~vazirani/NB-Berkeley.ppt.

For more information, please contact
Alex Wong: shw001@ucsd.edu.