INSTITUTE FOR MATHEMATICAL BEHAVIORAL SCIENCE

  CONFERENCE ON

ADAPTIAVE SYSTEMS AND MECHANISM DESIGN

January 23-25, 2009

  ABSTRACTS  

 

 

Kenneth Arrow  

"Questions about adaptation."

My purpose is simply to clarify or obscure the meaning of such terms as, "(complex) adaptive systems."  (1) Does "adaptation" simply mean, "reaction," or does it have a value implication? {2) What is the relation between adaptive reactions of parts of the system and adaptation of the system as a whole? (3) How is "adaptation" related to such other terms as, "resilience,"  "stability," or, "robustness"?   (4) How is "adaptation" related to "path dependence"? (5) How is "adaptation" related to "technological change" or to "evolution"?  (6) Is "adaptation" good or bad? Does this question make any sense?   As Alan Greenspan said to Congress, "if you think what I have said is clear, then you have not followed me."

Dirk Bergemann  

Robust Mechanism Design and Implementation, (joint with Stephen Morris, Princeton University )

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.

 

Asu Ozdaglar 

Spread of Information and Misinformation in Social Networks
 
This talk discusses how misinformation can affect beliefs among a group of agents and how it interacts with information aggregation. We first show that in social networks where agents involve in Bayesian updating, a finite number of individuals, even if they attempt to spread incorrect information, will have no effect on asymptotic beliefs under relatively mild conditions. This motivates a study of spread of misinformation in social networks where agents use reasonable rule of thumb learning rules. The bulk of the talk will investigate the impact of �influential agents� on the spread of misinformation as a function of network properties and the connectivity of the influential agents.
 

 

 

 

 

 

 

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