Quantization Games on Networks
Quantization Games on Networks
复制标题
网络量化游戏
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
A. Pentland
中科院分区：
文献类型：
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作者：
Ankur Mani;L. Varshney;A. Pentland
我们考虑一个网络量化器设计设置，其中代理必须在表示其本地源分布的保真度与成功与其他连接的代理进行通信的能力之间取得平衡。通过将该问题视为一个网络博弈，我们证明了纳什均衡量化器设计的存在性。对于任何智能体，在纳什均衡下，表示给定划分区域的词是该区域内局部和社会源概率分布混合的条件期望。此外，网络可以通过劳埃德-马克斯算法的分布式版本收敛到平衡状态。与语言进化的传统结果相反，我们发现在纳什均衡中可能存在多个词汇，每个个体恰好拥有其中一个词汇。对于频繁交流和拥有相似本地来源的个人来说，词汇表之间的重叠程度很高。最后，我们认为，当且仅当沟通链由具有共享词汇的代理组成时，翻译中的错误不会增加。
We consider a network quantizer design setting where agents must balance fidelity in representing their local source distributions against their ability to successfully communicate with other connected agents. By casting the problem as a network game, we show existence of Nash equilibrium quantizer designs. For any agent, under Nash equilibrium, the word representing a given partition region is the conditional expectation of the mixture of local and social source probability distributions within the region. Further, the network may converge to equilibrium through a distributed version of the Lloyd-Max algorithm. In contrast to traditional results in the evolution of language, we find several vocabularies may coexist in the Nash equilibrium, with each individual having exactly one of these vocabularies. The overlap between vocabularies is high for individuals that communicate frequently and have similar local sources. Finally, we argue error in translation along a chain of communication does not grow if and only if the chain consists of agents with shared vocabulary.