{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,3,29]],"date-time":"2022-03-29T21:36:47Z","timestamp":1648589807086},"reference-count":43,"publisher":"Cambridge University Press (CUP)","issue":"3","license":[{"start":{"date-parts":[[2014,7,22]],"date-time":"2014-07-22T00:00:00Z","timestamp":1405987200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AIEDAM"],"published-print":{"date-parts":[[2014,8]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>A computational approach for the design of self-organizing systems is proposed that employs a genetic algorithm to efficiently explore the vast space of possible configurations of a given system description. To generate the description of the system, a two-field based model is proposed in which agents are assigned parameterized responses to two \u201cfields,\u201d a task field encompassing environmental features and task objects, and a social field arising from agent interactions. The aggregate effect of these two fields, sensed by agents individually, governs the behavior of each agent, while the system-level behavior emerges from the actions of and interactions among the agents. Task requirements together with performance preferences are used to compose system fitness functions for evolving functional and efficient self-organizing mechanisms. Case studies on the evolutionary synthesis of self-organizing systems are presented and discussed. These case studies focus on achieving system-level behavior with minimal explicit coordination among agents. Agents were able to collectively display flocking, exploration, and foraging through self-organization. The proposed two-field model was able to capture important features of self-organizing systems, and the genetic algorithm was able to generate self-organizing mechanisms by which agents could form task-based structures to fulfill functional requirements.<\/jats:p>","DOI":"10.1017\/s0890060414000213","type":"journal-article","created":{"date-parts":[[2014,7,22]],"date-time":"2014-07-22T08:26:21Z","timestamp":1406017581000},"page":"259-275","source":"Crossref","is-referenced-by-count":6,"title":["Evolutionary computational synthesis of self-organizing systems"],"prefix":"10.1017","volume":"28","author":[{"given":"James","family":"Humann","sequence":"first","affiliation":[]},{"given":"Newsha","family":"Khani","sequence":"additional","affiliation":[]},{"given":"Yan","family":"Jin","sequence":"additional","affiliation":[]}],"member":"56","published-online":{"date-parts":[[2014,7,22]]},"reference":[{"key":"S0890060414000213_ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-3643-4"},{"key":"S0890060414000213_ref42","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-33902-8_5"},{"key":"S0890060414000213_ref23","volume-title":"Out of Control: The New Biology of Machines, Social Systems and the Economic World","author":"Kelly","year":"1994"},{"key":"S0890060414000213_ref21","unstructured":"Jin Y. , & Chen C. (2012). Field based behavior regulation for self-organization in cellular systems. Proc. Design Computing and Cognition Conf. DCC'12."},{"key":"S0890060414000213_ref1","first-page":"83","article-title":"Requisite variety and its implications for the control of complex systems","volume":"1","author":"Ashby","year":"1958","journal-title":"Cybernetica"},{"key":"S0890060414000213_ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TRA.2002.804502"},{"key":"S0890060414000213_ref26","doi-asserted-by":"publisher","DOI":"10.1016\/0167-2789(94)90293-3"},{"key":"S0890060414000213_ref40","doi-asserted-by":"crossref","unstructured":"Ueyama T. , Fukuda T. , & Arai F. (1992). Structure configuration using genetic algorithm for cellular robotic system. Proc. IEEE\/RSJ Int. Conf. Intelligent Systems, Vol. 3, p. 1542.","DOI":"10.1109\/IROS.1992.594219"},{"key":"S0890060414000213_ref2","first-page":"141","volume-title":"Morphogenetic Engineering: Toward Programmable Complex Systems","author":"Bai","year":"2012"},{"key":"S0890060414000213_ref15","volume-title":"Genetic Algorithms in Search, Optimization, and Machine Learning","author":"Goldberg","year":"1989"},{"key":"S0890060414000213_ref10","first-page":"1077","volume-title":"Proc. ASME 2011 Int. Design Engineering Technical Conf. and Computers and Information in Engineering Conf.","author":"Chiang","year":"2011"},{"key":"S0890060414000213_ref29","doi-asserted-by":"publisher","DOI":"10.1145\/37402.37406"},{"key":"S0890060414000213_ref39","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-77612-3"},{"key":"S0890060414000213_ref6","volume-title":"Digital Biology: How Nature Is Transforming Our Technology and Our Lives","author":"Bentley","year":"2001"},{"key":"S0890060414000213_ref3","first-page":"181","volume-title":"From Local Actions to Global Tasks: Stigmergy and Collective Robotics","author":"Beckers","year":"1994"},{"key":"S0890060414000213_ref4","unstructured":"Beni G. (1988). The concept of cellular robotic system. Proc. IEEE Int. Symp. Intelligent Control, 1988, pp. 57\u201362."},{"key":"S0890060414000213_ref7","doi-asserted-by":"publisher","DOI":"10.1007\/11734680_4"},{"key":"S0890060414000213_ref8","volume-title":"Proc. ASME 2011 Int. Design Engineering Technical Conf. and Computers and Information in Engineering Conf.","author":"Chen","year":"2011"},{"key":"S0890060414000213_ref9","unstructured":"Chiang W. (2012). A meta-interaction model for designing cellular self-organizing systems. PhD Thesis. University of Southern California, Los Angeles."},{"key":"S0890060414000213_ref38","volume-title":"Organizations in Action","author":"Thompson","year":"1967"},{"key":"S0890060414000213_ref11","unstructured":"Crutchfield J.P. , Mitchell M. , & Das R. (1996). Evolving cellular automata with genetic algorithms: a review of recent work. Proc. 1st Int. Conf. Evolutionary Computation and Its Applications, Moscow."},{"key":"S0890060414000213_ref14","doi-asserted-by":"crossref","unstructured":"Doursat R. (2011). The myriads of Alife: importing complex systems and self-organization into engineering. Proc. 2011 IEEE Symposium on Artificial Life, ALIFE, pp. 1\u20138.","DOI":"10.1109\/ALIFE.2011.5954671"},{"key":"S0890060414000213_ref19","doi-asserted-by":"crossref","DOI":"10.7551\/mitpress\/1090.001.0001","volume-title":"Adaptation in Natural and Artificial Systems: An Introductory Analysis With Applications to Biology, Control, and Artificial Intelligence","author":"Holland","year":"1992"},{"key":"S0890060414000213_ref20","doi-asserted-by":"crossref","unstructured":"Humann J. , & Jin Y. (2013). Evolutionary design of cellular self-organizing systems. Proc. ASME 2013 Int. Design Engineering Technical Conf. Computers and Information in Engineering Conf., Portland, OR.","DOI":"10.1115\/DETC2013-12485"},{"key":"S0890060414000213_ref30","article-title":"U.S. to propose vehicle-to-vehicle, crash-avoidance systems","author":"Rogers","year":"2014","journal-title":"Wall Street Journal"},{"key":"S0890060414000213_ref22","doi-asserted-by":"publisher","DOI":"10.1115\/1.2757190"},{"key":"S0890060414000213_ref24","first-page":"349","volume-title":"Biology of Termites: A Modern Synthesis","author":"Korb","year":"2011"},{"key":"S0890060414000213_ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2012.6224638"},{"key":"S0890060414000213_ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-32650-9_32"},{"key":"S0890060414000213_ref36","unstructured":"Stonedahl F. , & Wilensky U. (2010). Finding forms of flocking: evolutionary search in ABM parameter-spaces. Proc. MABS Workshop, 9th Int. Conf. Autonomous Agents and Multi-Agent Systems."},{"key":"S0890060414000213_ref5","first-page":"35","volume-title":"Proc. Genetic and Evolutionary Computation Conf.","author":"Bentley","year":"1999"},{"key":"S0890060414000213_ref41","first-page":"337","volume-title":"Proc. 14th Int. Conf. Genetic and Evolutionary Computation Conf. Companion","author":"Van Berkel","year":"2012"},{"key":"S0890060414000213_ref27","doi-asserted-by":"publisher","DOI":"10.1117\/12.417331"},{"key":"S0890060414000213_ref43","doi-asserted-by":"publisher","DOI":"10.1109\/MIS.2006.25"},{"key":"S0890060414000213_ref45","volume-title":"NetLogo Flocking Model","author":"Wilensky","year":"1998"},{"key":"S0890060414000213_ref46","doi-asserted-by":"publisher","DOI":"10.1115\/DETC2008-50102"},{"key":"S0890060414000213_ref47","unstructured":"Zouein G. , Chen C. , & Jin Y. (2010). Create adaptive systems through \u201cDNA\u201d guided cellular formation. Proc. Design Creativity 2010."},{"key":"S0890060414000213_ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TAC.2007.895842"},{"key":"S0890060414000213_ref32","doi-asserted-by":"crossref","unstructured":"Sadjadi F. (2004). Comparison of fitness scaling functions in genetic algorithms with applications to optical processing. In Optical Science and Technology: The SPIE 49th Annual Meeting, pp. 356\u2013364. Denver, CO: International Society for Optics and Photonics.","DOI":"10.1117\/12.563910"},{"key":"S0890060414000213_ref44","volume-title":"NetLogo","author":"Wilensky","year":"1998"},{"key":"S0890060414000213_ref17","volume-title":"Proc. Robosphere","author":"Goldstein","year":"2004"},{"key":"S0890060414000213_ref18","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-642-96469-5","volume-title":"Synergetics: An Introduction: Nonequilibrium Phase Transitions and Self-Organization in Physics, Chemistry, and Biology","author":"Haken","year":"1978"},{"key":"S0890060414000213_ref35","doi-asserted-by":"publisher","DOI":"10.1017\/S0890060405050110"}],"container-title":["Artificial Intelligence for Engineering Design, Analysis and Manufacturing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S0890060414000213","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,8,22]],"date-time":"2020-08-22T13:12:33Z","timestamp":1598101953000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S0890060414000213\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,7,22]]},"references-count":43,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2014,8]]}},"alternative-id":["S0890060414000213"],"URL":"https:\/\/doi.org\/10.1017\/s0890060414000213","relation":{},"ISSN":["0890-0604","1469-1760"],"issn-type":[{"value":"0890-0604","type":"print"},{"value":"1469-1760","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,7,22]]}}}