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Asynchronous Learning with Limited Information: An Experimental Analysis

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Author Info
Barry Sopher () (Rutgers University)
Eric Friedman () (Rutgers University)
Scott Shenker () (ICSI, Berkeley)
Mikhael Shor () (Rutgers University)

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Abstract

We present the results of an experiment on learning in a continuous-time low-information setting. For a Cournot oligopoly with differentiated products, a dominance solvable game, we find little evidence of convergence to the Nash equilibrium. In an asynchronous setting, play tends toward the Stackelberg outcome. Convergence is significantly more robust for a "Serial Cost Sharing" game, which satisfies a stronger solution concept of overwhelmed solvability. However, as the number of players grows, this improved convergence tends to diminish. This seems to be driven by high and correlated experimentation or noise and demonstrates that even when play converges, the convergence times may be too long to be of practical significance.

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Publisher Info
Paper provided by Rutgers University, Department of Economics in its series Departmental Working Papers with number 200022.

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Date of creation: 25 Oct 2000
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Handle: RePEc:rut:rutres:200022

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Related research
Keywords: learning;

Find related papers by JEL classification:
C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

Cited by:
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  1. Mikhael Shor, 2003. "Learning to Respond: The Use of Heuristics in Dynamic Games," Game Theory and Information 0301001, EconWPA. [Downloadable!]
Statistics
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This page was last updated on 2009-10-18.


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