Learning efficient Nash equilibria in distributed systems
An individual's learning rule is completely uncoupled if it does not depend on the actions or payoffs of anyone else. We propose a variant of log linear learning that is completely uncoupled and that selects an efficient pure Nash equilibrium in all generic n-person games that possess at least...
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| Format: | Working paper |
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University of Oxford
2010
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