Toward a novel design of swarm robots based on the dynamic Bayesian network

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1 被引用数 (Scopus)

抄録

In this chapter, we describe a novel design method of swarm robots based on the dynamic Bayesian network. Recently, an increasing attention has been paid to swarm robots due to their scalability, flexibility, cost-performance, and robustness. Designing swarm robots so that they exhibit intended collective behaviors is considered as the most challenging issue and so far ad-hoc methods which heavily rely on extensive experiments are common. Such a method typically faces a huge amount of data and handles them possibly using machine learning methods such as clustering.We argue, however, that a more principled use of data with a probabilistic model is expected to lead to a reduced number of experiments in the design and propose the fundamental part of the approach. A simple but a real example using two swarm robots is described as an application.

本文言語英語
ホスト出版物のタイトルAdvances in Data Management
編集者Zbigniew Ras, Agnieszka Dardzinska
ページ299-310
ページ数12
DOI
出版ステータス出版済み - 2009

出版物シリーズ

名前Studies in Computational Intelligence
223
ISSN(印刷版)1860-949X

!!!All Science Journal Classification (ASJC) codes

  • 人工知能

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