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Network Formation with Adaptive Agents

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  • Schuster, Stephan

Abstract

In this paper, a reinforcement learning version of the connections game first analysed by Jackson and Wolinsky is presented and compared with benchmark results of fully informed and rational players. Using an agent-based simulation approach, the main nding is that the pattern of reinforcement learning process is similar, but does not fully converge to the benchmark results. Before these optimal results can be discovered in a learning process, agents often get locked in a state of random switching or early lock-in.

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File URL: http://mpra.ub.uni-muenchen.de/27388/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 27388.

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Date of creation: 2010
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Handle: RePEc:pra:mprapa:27388

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Keywords: agent-based computational economics; strategic network formation; network games; reinforcement learning;

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