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Constructing shared interpretations in a team of intelligent agents: the effects of communication intensity and structure

机译：在智能代理团队中构建共享解释：沟通强度和结构的影响

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摘要

In this paper we explore a model of a team of intelligent agents constructing a shared interpretation of the state of their environment. Each agent is modeled as a constraint satisfaction network of the Hopfield (1982) type.rnWe show that in a noisy environment communication intensity often has a nonmonotonic effect on team interpretive accuracy. We also investigate how team communication can correct erroneous individual interpretations stored in agents' memories - errors concerning what they know, not only what they perceive.rnWe also compare the effects of different communication structures, and show that communication structure matters only when agents are cognitively heterogeneous (each has a different repertoire of interpretations in his memory), while it has only a minor impact on team performance when agents are homogeneous.
机译：在本文中，我们探索了一个智能代理团队的模型，该模型构建了对其环境状态的共享解释。每个主体都被建模为Hopfield（1982）类型的约束满足网络。rn我们表明，在嘈杂的环境中，沟通强度通常对团队的解释准确性具有非单调的影响。我们还研究了团队沟通如何纠正存储在特工记忆中的错误个人解释-有关他们所知道的错误，不仅涉及他们所感知的错误.rn我们还比较了不同沟通结构的影响，并表明沟通结构仅在特工具有认知能力时才重要异质的（每个人在他的记忆中都有不同的解释），而当特工是同质的时，对团队绩效的影响很小。

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