一种具有时间约束的不精确移动智能体路线确定的自适应方法

Luciana Rech, C. Montez, R. S. Oliveira
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引用次数: 0

摘要

在具有时间要求的基于移动代理的分布式应用环境中,确定代理行程的算法是最基本的。为了确定代理人的行程,有必要考虑在达到高质量结果和满足确定的最后期限之间的权衡。在本文中,我们描述和评估了两种自适应启发式,它们在智能体的任务开始时对其行为做出决策。关于行为的决策是基于移动代理在过去执行中收集的利益日志。代理人在离开时进行自我调整。一旦选择了特定任务的行为,代理将保持该行为直到任务结束。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An adaptive approach for the determination of the itinerary of imprecise mobile agents with timing constraints
Algorithms to determine the itinerary of agents are fundamental in the context of distributed applications based on mobile agents with timing requirements. To establish an agent's itinerary it is necessary to consider the trade-offs between achieving high-quality results while meeting firm deadlines. In this paper we describe and evaluate two adaptive heuristics that make a decision about the behavior for an agent at the beginning of its mission. The decision-making about the behavior is based on a log of benefits collected by the mobile agent in past executions. An agent adapts itself at the departure. Once chosen the behavior for a particular mission, the agent keeps this behavior until the end of the mission.
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