Asynchronous Learning with Limited Information: An Experimental Analysis

Barry Sopher, Eric Friedman (), Scott Shenker () and Mikhael Shor
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Eric Friedman: Rutgers University
Scott Shenker: ICSI, Berkeley

Departmental Working Papers from Rutgers University, Department of Economics

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.

Keywords: learning (search for similar items in EconPapers)
JEL-codes: C91 (search for similar items in EconPapers)
Date: 2000-10-25
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:rut:rutres:200022

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