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Achieving Pareto Optimality Through Distributed Learning.

Abstract:

We propose a simple payoff-based learning rule that is completely decentralized, and that leads to an efficient configuration of actions in any n-person game with generic payoffs. The algorithm requires no communication. Agents respond solely to changes in their own realized payoffs, which are affected by the actions of other agents in the system in ways that they do not generally understand. The method has potential application to the optimization of complex systems with many distributed ...

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Publisher:
Department of Economics (University of Oxford)
Series:
Discussion paper series
Publication date:
2011-01-01
Language:
English
UUID:
uuid:cb98a552-448b-4f53-87da-730421921bdd
Local pid:
oai:economics.ouls.ox.ac.uk:15269
Deposit date:
2011-12-15

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