用于地形覆盖的Scout-explorer多智能体框架

Nilay Binjola, J. P. Misra
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引用次数: 1

摘要

多代理系统使我们能够模拟群体行为,其中智能来自集体而不是个人。地形覆盖问题是多智能体系统中一个重要的研究领域,具有广泛的实际应用。我们提出了一种新的多智能体框架,称为Scout-Explorer框架,该框架利用全局地形知识覆盖以前未知的地形,同时节能。本文展示了通过多个度量将标准地形覆盖算法与所提出框架的时空实现进行比较的模拟结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Scout-explorer multi-agent framework for terrain coverage
Multi-Agent systems enable us to simulate swarm behaviour wherein intelligence emerges from the collective instead of the individual. The problem of terrain coverage forms a prominent field of research in multi-agent systems with wide-ranging real-life applications. We propose a new multi-agent framework called the Scout-Explorer framework which utilizes global terrain knowledge to cover a previously unknown terrain while being energy effective. The paper demonstrates results obtained via simulations over multiple metrics comparing standard terrain coverage algorithms with a spatiotemporal implementation of the proposed framework.
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