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Decentralized learning automata (DLA) consist of a large number of learning automata (LAs), which learn independently without information exchange among them. However, although these LAs are able to reach Nash equilibrium theoretically, their learning efficiencies are weakened drastically since each LA works under nonstationary environment instead of stationary environment. In order to coordinate...
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