{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T04:04:26Z","timestamp":1777521866117,"version":"3.51.4"},"reference-count":18,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2007,9,1]],"date-time":"2007-09-01T00:00:00Z","timestamp":1188604800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Adaptive Behavior"],"published-print":{"date-parts":[[2007,9]]},"abstract":"<jats:p>This article presents a simple adaptation mechanism to automatically adjust the ratio of foragers to resters (division of labor) in a swarm of foraging robots and hence maximize the net energy income to the swarm. Three adaptation rules are introduced based on local sensing and communications. Individual robots use internal cues (successful food retrieval), environmental cues (collisions with team-mates while searching for food) and social cues (team-mate success in food retrieval) to dynamically vary the time spent foraging or resting. Simulation results show that the swarm demonstrates successful adaptive emergent division of labor and robustness to environmental change (in food source density), and we observe that robots need to cooperate more when food is scarce. Furthermore, the adaptation mechanism is able to guide the swarm towards energy optimization despite the limited sensing and communication abilities of the individual robots and the simple social interaction rules. The swarm also exhibits the capacity to collectively perceive environmental changes; a capacity that can only be observed at a group level and cannot be deduced from individual robots.<\/jats:p>","DOI":"10.1177\/1059712307082088","type":"journal-article","created":{"date-parts":[[2007,8,29]],"date-time":"2007-08-29T03:39:30Z","timestamp":1188358770000},"page":"289-305","source":"Crossref","is-referenced-by-count":103,"title":["Towards Energy Optimization: Emergent Task Allocation in a Swarm of Foraging Robots"],"prefix":"10.1177","volume":"15","author":[{"given":"Wenguo","family":"Liu","sequence":"first","affiliation":[{"name":"Bristol Robotics Lab, University of the West of England, Bristol, UK,"}]},{"given":"Alan F. T.","family":"Winfield","sequence":"additional","affiliation":[{"name":"Bristol Robotics Lab, University of the West of England, Bristol, UK"}]},{"given":"Jin","family":"Sa","sequence":"additional","affiliation":[{"name":"Bristol Robotics Lab, University of the West of England, Bristol, UK"}]},{"given":"Jie","family":"Chen","sequence":"additional","affiliation":[{"name":"Intellectual Information Technology Lab, Beijing Institute of Technology, China"}]},{"given":"Lihua","family":"Dou","sequence":"additional","affiliation":[{"name":"Intellectual Information Technology Lab, Beijing Institute of Technology, China"}]}],"member":"179","published-online":{"date-parts":[[2007,9,1]]},"reference":[{"key":"atypb1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-30552-1_1"},{"key":"atypb2","doi-asserted-by":"publisher","DOI":"10.1093\/oso\/9780195131581.001.0001"},{"key":"atypb3","doi-asserted-by":"publisher","DOI":"10.1515\/9780691212920"},{"key":"atypb4","volume-title":"Proceedings of the International Conference on Advanced Robotics","author":"Gerkey, B.P."},{"key":"atypb5","first-page":"111","volume":"100","author":"Guerrero, J.","year":"2003","journal-title":"Artificial Research and Development in Frontiers in Artificial Intelligence and Applications"},{"key":"atypb6","doi-asserted-by":"publisher","DOI":"10.1162\/106454699568737"},{"key":"atypb7","volume-title":"Proceedings of the IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)","author":"Jones, C."},{"key":"atypb8","first-page":"65","volume":"30","author":"Krieger, M.J.B.","year":"2000","journal-title":"Systems"},{"key":"atypb9","first-page":"4","volume":"1","author":"Labella, T.H.","year":"2006","journal-title":"Systems"},{"key":"atypb10","doi-asserted-by":"publisher","DOI":"10.1023\/A:1019633424543"},{"key":"atypb11","volume-title":"Swarm intelligence in autonomous collective robotics: from tools to the analysis and synthesis of distributed collective strategies","author":"Martinoli, A.","year":"1999"},{"key":"atypb12","doi-asserted-by":"publisher","DOI":"10.1177\/0278364904042197"},{"key":"atypb13","volume-title":"From Animals to Animats 7: Proceedings of the Seventh International Conference on Simulation of Adaptive Behavior","author":"Nembrini, J."},{"key":"atypb14","volume-title":"Proceedings of the 5th International Conference on Autonomous Agents","author":"stergaard, E.H."},{"key":"atypb15","doi-asserted-by":"crossref","unstructured":"Rosenfeld, A.                 ,                      Kaminka, G.A. &                      Kraus, S.                  (2005). A study of scalability properties in robotic                 teams . In                      P. Scerri                 ,                      R. Vincent                 , &                      R. Mailler                  (Eds.) Coordination of large-scale multi-agent systems (pp.                 27\u201451).                      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