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A socially-based distributed self-organizing algorithm for holonic multi-agent systems: Case study in a task environment

机译:完整的多智能体系统基于社会的分布式自组织算法:任务环境中的案例研究

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Holonic multi-agent systems (HMASs) have recently attracted many researches in multi-agent systems community. Inspired from the multi-level and self-similar structures of social and biological system, holonic multi-agent systems have been widely used to model and solve complex real-world problems. The main concern in deploying HMASs is the problem of building the hierarchical holonic structure, called holarchy, and dynamically managing it during its lifetime. The way an HMAS is organized has a great impact on its applicability and performance. This paper proposes a self-organizing algorithm to build and manage the holoic structures in multi-agent systems. This algorithm is based on the local information of the agents about other agents they can communicate with. Using common social concepts, like skills, diversity, social exchange theory, and norms in definition of the algorithm, the outcomes of this research can be used in wide ranges of distributed applications. The proposed model is extensively tested in a task allocation problem; and its performance based on various design parameters is studied. Empirical results show that the proposed model properly increases the performance of the system in terms of effectiveness and efficiency. (C) 2016 Elsevier B.V. All rights reserved.
机译:全息多智能体系统(HMAS)最近吸引了多智能体系统社区的许多研究。受社会和生物系统的多层次和自相似结构的启发,完整的多智能体系统已被广泛用于建模和解决复杂的现实世界问题。部署HMAS的主要关注点是建立分层的整体结构(称为整体性)并在其生命周期内对其进行动态管理的问题。 HMAS的组织方式对其适用性和性能有很大影响。本文提出了一种自组织算法来构建和管理多智能体系统中的整体结构。此算法基于代理的本地信息,这些本地信息是关于它们可以与之通信的其他代理的信息。使用常见的社会概念,例如技能,多样性,社会交流理论和算法定义中的规范,这项研究的结果可用于广泛的分布式应用程序。该模型在任务分配问题中得到了广泛的测试。并研究了基于各种设计参数的性能。实证结果表明,所提出的模型在有效性和效率方面适当地提高了系统的性能。 (C)2016 Elsevier B.V.保留所有权利。

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