Theoretical foundations for multiple rendezvous of glowworm-inspired mobile agents with variable local-decision domains

K. Krishnanand, Debasish Ghose
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引用次数: 27

Abstract

We present the theoretical foundations for the multiple rendezvous problem involving design of local control strategies that enable groups of visibility-limited mobile agents to split into subgroups, exhibit simultaneous taxis behavior towards, and eventually rendezvous at, multiple unknown locations of interest. The theoretical results are proved under certain restricted set of assumptions. The algorithm used to solve the above problem is based on a glowworm swarm optimization (GSO) technique, developed earlier, that finds multiple optima of multimodal objective functions. The significant difference between our work and most earlier approaches to agreement problems is the use of a virtual local-decision domain by the agents in order to compute their movements. The range of the virtual domain is adaptive in nature and is bounded above by the maximum sensor/visibility range of the agent. We introduce a new decision domain update rule that enhances the rate of convergence by a factor of approximately two. We use some illustrative simulations to support the algorithmic correctness and theoretical findings of the paper
具有可变局部决策域的萤火虫启发移动智能体多交会的理论基础
我们提出了多重会合问题的理论基础,包括局部控制策略的设计,使能见度有限的移动代理群体能够分成子群体,同时表现出向多个未知感兴趣的地点的出租车行为,并最终在多个未知地点会合。在一定的限制条件下证明了理论结果。用于解决上述问题的算法是基于先前开发的萤火虫群优化(GSO)技术,该技术寻找多模态目标函数的多个最优。我们的工作与大多数早期解决协议问题的方法之间的显著区别在于,代理使用虚拟的局部决策域来计算它们的运动。虚拟域的范围本质上是自适应的,并且由代理的最大传感器/可见范围限制。我们引入了一种新的决策域更新规则,将收敛速度提高了大约两倍。我们用一些说明性的模拟来支持算法的正确性和本文的理论发现
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