{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T19:36:34Z","timestamp":1766086594877,"version":"3.41.2"},"reference-count":28,"publisher":"Emerald","issue":"4","license":[{"start":{"date-parts":[[2009,11,20]],"date-time":"2009-11-20T00:00:00Z","timestamp":1258675200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2009,11,20]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-heading\">Purpose<\/jats:title><jats:p>In evolutionary robotics (ER), robotic control systems are subject to a developmental process inspired by natural evolution. The purpose of this paper is to utilize a control system representation based on finite state machines (FSMs) to build a decentralized online\u2010evolutionary framework for swarms of mobile robots.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Design\/methodology\/approach<\/jats:title><jats:p>A new recombination operator for multi\u2010parental generation of offspring is presented and a known mutation operator is extended to harden parts of genotypes involved in good behavior, thus narrowing down the dimensions of the search space. A storage called memory genome for archiving the best genomes of every robot introduces a decentralized elitist strategy. These operators are studied in a factorial set of experiments by evolving two different benchmark behaviors such as collision avoidance and gate passing on a simulated swarm of robots. A comparison with a related approach is provided.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Findings<\/jats:title><jats:p>The framework is capable of robustly evolving the benchmark behaviors. The memory genome and the number of parents for reproduction highly influence the quality of the results; the recombination operator leads to an improvement in certain parameter combinations only.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Research limitations\/implications<\/jats:title><jats:p>Future studies should focus on further improving mutation and recombination. Generality statements should be made by studying more behaviors and there is a need for experimental studies with real robots.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Practical implications<\/jats:title><jats:p>The design of decentralized ER frameworks is improved.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title><jats:p>The framework is robust and has the advantage that the resulting controllers are easier to analyze than in approaches based on artificial neural networks. The findings suggest improvements in the general design of decentralized ER frameworks.<\/jats:p><\/jats:sec>","DOI":"10.1108\/17563780911005845","type":"journal-article","created":{"date-parts":[[2009,11,14]],"date-time":"2009-11-14T07:05:06Z","timestamp":1258182306000},"page":"695-723","source":"Crossref","is-referenced-by-count":35,"title":["Decentralized evolution of robotic behavior using finite state machines"],"prefix":"10.1108","volume":"2","author":[{"given":"Lukas","family":"K\u00f6nig","sequence":"first","affiliation":[]},{"given":"Sanaz","family":"Mostaghim","sequence":"additional","affiliation":[]},{"given":"Hartmut","family":"Schmeck","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"key":"key2022020220025883800_b1","unstructured":"Ampatzis, C., Tuci, E., Trianni, V. and Dorigo, M. (2005), \u201cEvolving communicating agents that integrate information over time: a real robot experiment\u201d, CD\u2010ROM Proceedings of the 7th International Conference on Artificial Evolution (EA 2005), Springer, Berlin."},{"key":"key2022020220025883800_b2","unstructured":"Ampatzis, C., Tuci, E., Trianni, V. and Dorigo, M. (2006), \u201cEvolution of signalling in a group of robots controlled by dynamic neural networks\u201d, in Sahin, E., Spears, W.M. and Winfield, A.F.T. (Eds), Proceedings of the 2nd Workshop on Swarm Robotics, Springer, Berlin."},{"key":"key2022020220025883800_b3","doi-asserted-by":"crossref","unstructured":"Bonabeau, E., Theraulaz, G. and Dorigo, M. (1999), Swarm Intelligence: From Natural to Artificial Systems (Santa Fe Institute Studies in the Sciences of Complexity), Oxford University Press, New York, NY.","DOI":"10.1093\/oso\/9780195131581.001.0001"},{"key":"key2022020220025883800_b4","unstructured":"Braitenberg, V. 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(1995), \u201cAn evolutionary programming approach to self\u2010adaptation on finite state machines\u201d, Proceedings of the 4th Annual Conference on Evolutionary Programming, The MIT Press, Cambridge, MA, pp. 355\u201065."},{"key":"key2022020220025883800_b6","unstructured":"Fogel, L.J., Owens, A.J. and Walsh, M.J. (1966), Artificial Intelligence through Simulated Evolution, Wiley, New York, NY."},{"key":"key2022020220025883800_b10","doi-asserted-by":"crossref","unstructured":"Gro\u00df, R. and Dorigo, M. (2004), \u201cCooperative transport of objects of different shapes and sizes\u201d, Ant Colony Optimization and Swarm Intelligence, 4th International Workshop, Springer, Berlin, pp. 106\u201017.","DOI":"10.1007\/978-3-540-28646-2_10"},{"key":"key2022020220025883800_b11","doi-asserted-by":"crossref","unstructured":"Hartland, C. and Bredeche, N. 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