Descripción
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We introduce a diffusion-based algorithm in which multiple agents cooperate to predict a common and global statevalue function by sharing local estimates and local gradient information among neighbors. Our algorithm is a fully distributed implementation of the gradient temporal difference with linear function approximation, to make it applicable to multiagent settings. Simulations illustrate the benefit of cooperation in learning, as made possible by the proposed algorithm. | |
Internacional
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Si |
Nombre congreso
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2012 3rd International Workshop on Cognitive Incromation Processing (CIP) |
Tipo de participación
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960 |
Lugar del congreso
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Revisores
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Si |
ISBN o ISSN
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978-1-4673-1878-5 |
DOI
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Fecha inicio congreso
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28/05/2012 |
Fecha fin congreso
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30/05/2012 |
Desde la página
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1 |
Hasta la página
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6 |
Título de las actas
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3rd International Workshop on Cognitive Incromation Processing (CIP) |