随机定位对象的新搜索算法:一种基于非合作智能体的方法

D. Calitoiu
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引用次数: 12

摘要

在本文中,我们解决了一个普遍的问题,即什么是有效搜索随机定位对象(目标站点)的最佳策略。我们提出了一种新的基于智能体的在不可预测环境下的搜索算法。我们工作的独创性在于应用非合作策略,即分布式Goore博弈模型,而不是应用经典的合作和竞争策略或个人策略。本文只讨论agent多次访问同一目标时发生的非破坏性搜索。非破坏性搜索可以在两种情况下进行:如果目标暂时不活动,或者如果目标离开该区域。提出的算法有两种版本,一种是智能体以等于1的步长移动,另一种是智能体的步长服从Levy飞行分布。后一个版本的灵感来自A.M.的作品雷诺兹,受到生物学例子的启发。
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New search algorithm for randomly located objects: A non-cooperative agent based approach
In this paper we address the general question of what is the best strategy to search efficiently for randomly located objects (target sites). We propose a new agent based algorithm for searching in an unpredictable environment. The originality of our work consists in applying a non-cooperative strategy, namely the distributed Goore Game model, as opposed to applying the classical collaborative and competitive strategies, or individual strategies. This paper covers only the non-destructive search that occurs when the agent visits the same target many times. The nondestructive search can be performed in either of the two cases: if the target becomes temporarily inactive or if it leaves the area. The proposed algorithm has two versions: one when the agent can move with a step equal to unity and the other when the step of the agent follows a Levy flight distribution. The latter version is inspired by the work of A.M. Reynolds, motivated by biological examples.
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