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Exploring Social Networks in Request for Proposal Dynamic Coalition Formation Problems

机译:探索社交网络,要求提出动态联盟形成问题

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In small scale multi-agent environments, every agent is aware of all of the others. This allows agents to evaluate the potential outcomes of their interaction for each of their possible interaction partners. However, this farsighted knowledge becomes an issue in large scale systems, leading to a combinatorial explosion in evaluation and is unrealistic in communication terms. Limited awareness of other agents is therefore the only plausible scenario in many large-scale environments. This limited awareness can be modeled as a sparse social network in which agents only interact with a limited subset of agents known to them. In this paper, we explore a model of dynamic multi-agent coalition formation in which agents are connected via fixed underlying social networks that exhibit different well known structures such as Small World, Random and Scale Free topologies. Agents follow different exploratory policies and are distributed in the network according to a variety of metrics. The primary results of the paper are to demonstrate different positive and negative properties of each topology for the coalition formation problem. In particular we show that despite positive properties for many problems, Small World topologies introduce blocking factors which hinder the emergence of good coalition solutions in many configurations.
机译:在小规模的多代理环境中,每个代理都知道所有其他代理。这使得代理商可以评估他们对他们每个可能的互动伙伴的互动的潜在结果。然而,这种远视知识成为大规模系统中的问题,导致评估中的组合爆炸,并且在通信条款中是不现实的。因此,对其他代理的意识有限是许多大型环境中唯一合理的情景。这种有限的感知可以被建模为稀疏的社交网络,其中代理只与他们已知的有限代理的子集进行交互。在本文中,我们探讨了动态多代理联盟形成的模型,其中代理通过固定的底层社交网络连接,该网络具有不同众所周知的结构,如小世界,随机和规模的自由拓扑。代理遵循不同的探索性政策,并根据各种指标在网络中分发。本文的主要结果是对联盟形成问题的每种拓扑的不同阳性和阴性特性。特别是我们表明,尽管许多问题存在积极性质,但小世界拓扑拓展引入了阻碍了许多配置中良好联盟解决方案的出现的阻塞因素。

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