Consensus based on learning game theory

机译：基于学习博弈论的共识

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摘要

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.

机译：本文基于虚构的戏法提出了一种系统分布式优化方法。在博弈论框架下证明了算法的收敛性。结果相当于共识问题。它介绍了一种研究共识问题的新颖视角。这些等价由数值案例说明。

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来源
《IEEE Chinese Guidance, Navigation and Control Conference》|2014年||共6页
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Zhongjie Lin; Liu Hugh H. T.;
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正文语种
中图分类飞行控制系统与导航;
关键词
game theory; learning (artificial intelligence); optimisation; consensus; distributed optimization; fictitious play concept; learning game theory; Algorithm design and analysis; Convergence; Equations; Game theory; Games; Mathematical model; Optimization;

机译：博弈论;学习（人工智能）;优化;共识;分布式优化;虚构的戏剧概念;学习博弈论;算法设计和分析;融合;方程式;游戏理论;游戏;数学模型;优化;优化;优化;优化;

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机译：基于学习博弈论与无人机会合应用的共识

Consensus based on learning game theory

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