2022年
Iterative shepherding control for agents with heterogeneous responsivity
Mathematical Biosciences and Engineering
- ,
- ,
- 巻
- 19
- 号
- 4
- 開始ページ
- 3509
- 終了ページ
- 3525
- 記述言語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.3934/mbe.2022162
- 出版者・発行元
- American Institute of Mathematical Sciences (AIMS)
<p lang="fr"><abstract><p>In the context of the theory of multi-agent systems, the shepherding problem refers to designing the dynamics of a herding agent, called a sheepdog, so that a given flock of agents, called sheep, is guided into a goal region. Although several effective methodologies and algorithms have been proposed in the last decade for the shepherding problem under various formulations, little research has been directed to the practically important case in which the flock contains sheep agents unresponsive to the sheepdog agent. To fill in this gap, we propose a sheepdog algorithm for guiding unresponsive sheep in this paper. In the algorithm, the sheepdog iteratively applies an existing shepherding algorithm, the farthest-agent targeting algorithm, while dynamically switching its destination. This procedure achieves the incremental growth of a controllable flock, which finally enables the sheepdog to guide the entire flock into the goal region. Furthermore, we illustrate by numerical simulations that the proposed algorithm can outperform the farthest-agent targeting algorithm.</p></abstract></p>
- リンク情報
- ID情報
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- DOI : 10.3934/mbe.2022162
- ISSN : 1551-0018