{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:31:41Z","timestamp":1760243501202,"version":"build-2065373602"},"reference-count":26,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2013,7,24]],"date-time":"2013-07-24T00:00:00Z","timestamp":1374624000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotics"],"abstract":"<jats:p>Swarming and modular robotic locomotion are two disconnected behaviours that a group of small homogeneous robots can be used to achieve. The use of these two behaviours is a popular subject in robotics research involving search, rescue and exploration. However, they are rarely addressed as two behaviours that can coexist within a single robotic system. Here, we present a bio-inspired decision mechanism, which provides a convenient way for evolution to configure the conditions and timing of behaving as a swarm or a modular robot in an exploration scenario. The decision mechanism switches among two behaviours that are previously developed (a pheromone-based swarm control and a sinusoidal rectilinear modular robot movement). We use Genetic Programming (GP) to evolve the controller for these decisions, which acts without a centralized mechanism and with limited inter-robot communication. The results show that the proposed bio-inspired decision mechanism provides an evolvable medium for the GP to utilize in evolving an effective decision-making mechanism.<\/jats:p>","DOI":"10.3390\/robotics2030165","type":"journal-article","created":{"date-parts":[[2013,7,24]],"date-time":"2013-07-24T18:32:09Z","timestamp":1374690729000},"page":"165-184","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Hormone-Inspired Behaviour Switching for the Control of Collective Robotic Organisms"],"prefix":"10.3390","volume":"2","author":[{"given":"T\u00fcze","family":"Kuyucu","sequence":"first","affiliation":[{"name":"Engineering Department, Griffith Textile Machines, Washington NE38 8QA, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ivan","family":"Tanev","sequence":"additional","affiliation":[{"name":"Department of Information Systems Design, Doshisha University, Kyotanabe 610-0321, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Katsunori","family":"Shimohara","sequence":"additional","affiliation":[{"name":"Department of Information Systems Design, Doshisha University, Kyotanabe 610-0321, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2013,7,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"805","DOI":"10.1109\/TSMCB.2011.2178021","article-title":"A hierarchical gene regulatory network for adaptive multi-robot pattern formation","volume":"42","author":"Jin","year":"2012","journal-title":"IEEE Trans. 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Mag."}],"container-title":["Robotics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2218-6581\/2\/3\/165\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:48:11Z","timestamp":1760219291000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2218-6581\/2\/3\/165"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,7,24]]},"references-count":26,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2013,9]]}},"alternative-id":["robotics2030165"],"URL":"https:\/\/doi.org\/10.3390\/robotics2030165","relation":{},"ISSN":["2218-6581"],"issn-type":[{"type":"electronic","value":"2218-6581"}],"subject":[],"published":{"date-parts":[[2013,7,24]]}}}