In this paper, a systematic distributed optimization approach is proposed based on a fictitious play concept. The convergence of the algorithm is proven under the game theory framework. The result is equivalent to a consensus problem. It introduces a novel perspective to study the consensus problem. Such an equivalence is illustrated by numerical cases.
Consensus based on learning game theory
01.08.2014
164755 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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