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We consider the El Farol bar problem (W. B. Arthur, The American Economic Review , 84(2): 406--411 (1994), D. Challet and Y.C. Zhang, Physica A , 256:514 (1998)) as an instance of the general problem of how to automatically configure a distributed dynamical system so that its nodal elements do not "work at cross purposes", in that their collective dynamical behavior successfully achieves a global goal. We present a summary of a mathematical theory for such automated configuration applicable when (as in the bar problem) the global goal can be expressed as minimizing a global energy function. We then investigate the applicability of the core concepts of that theory to a difficult variant of the bar problem. We show that a system designed in accord with that theory performs nearly optimally for the bar problem, and in particular avoids the tragedy of the commons for that problem.
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@article{wolpert-tumer_epl00, author = {D. H. Wolpert and K. Wheeler and K. Tumer}, title = {Collective Intelligence for Control of Distributed Dynamical Systems}, journal={Europhysics Letters}, volume = {49}, number = {6}, month = {March}, abstract = {We consider the El Farol bar problem (W. B. Arthur, The American Economic Review , 84(2): 406--411 (1994), D. Challet and Y.C. Zhang, Physica A , 256:514 (1998)) as an instance of the general problem of how to automatically configure a distributed dynamical system so that its nodal elements do not "work at cross purposes", in that their collective dynamical behavior successfully achieves a global goal. We present a summary of a mathematical theory for such automated configuration applicable when (as in the bar problem) the global goal can be expressed as minimizing a global energy function. We then investigate the applicability of the core concepts of that theory to a difficult variant of the bar problem. We show that a system designed in accord with that theory performs nearly optimally for the bar problem, and in particular avoids the tragedy of the commons for that problem.}, bib2html_pubtype = {Journal Articles}, bib2html_rescat = {Collectives}, year = {2000} }
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