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Bounded optimization of resource allocation among multiple agents using an organizational decision model

机译:使用组织决策模型对多个代理之间的资源分配进行有界的优化

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Multi-agent System (MAS) can be used to dispose bounded optimization problems with dynamically changing resources because its autonomous distributed management model aspect is fitted to dealing with such external disturbances. One of the problems in multi-agent optimizations is that it is difficult to rigorously define the optimization criteria with respect to the global optimization in advance. Rather, it may depend much on more situated factors such as temporal availability of resources and coexistence of current conflicts, conflicts among what has been already scheduled and what is to be scheduled. In this paper, an organizational model called Garbage Can Model (GCM) is introduced. In GCM, through its three decision-making strategies and the fluidities of problems and resources, solutions made by an individual agent are concerned with several agents that are co-existing in the environment. The problems allocated to each agent are solved not only by an agent's own efforts, but also by the change of problem solving status of other agents. Our simulation experiment shows that GCM is a preferred framework for multi-agent optimization problems in dealing with the above difficulties.
机译:多智能体系统(MAS)可以用来解决资源动态变化的有界优化问题,因为它的自治分布式管理模型方面适合处理此类外部干扰。多主体优化中的问题之一是,很难预先针对全局优化严格定义优化标准。而是,它可能很大程度上取决于更局限的因素,例如资源的时间可用性和当前冲突的共存,已经安排的计划与计划的计划之间的冲突。本文介绍了一种称为垃圾桶模型(GCM)的组织模型。在GCM中,通过其三种决策策略以及问题和资源的流动性,单个代理人提出的解决方案与环境中共存的几个代理人有关。分配给每个代理的问题不仅可以通过代理自己的努力来解决,而且可以通过其他代理的问题解决状态的改变来解决。我们的模拟实验表明,GCM是解决上述困难的多主体优化问题的首选框架。

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