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[null,"1.","Record Nr.",null,"UNINA9910483212703321"]
[null,null,"Autore",null,"Cuevas Erik"]
[null,null,"Titolo",null,"New Advancements in Swarm Algorithms: Operators and Applications / / by Erik Cuevas, Fernando Fausto, Adrián González"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020"]
[null,null,"ISBN",null,"3-030-16339-3"]
[null,null,"Edizione",null,"[1st ed. 2020.]"]
[null,null,"Descrizione fisica",null,"1 online resource (306 pages)"]
[null,null,"Collana",null,"Intelligent Systems Reference Library, , 1868-4408 ; ; 160"]
[null,null,"Disciplina",null,"511.8"]
[{"$nulls":4},"518.1"]
[null,null,"Soggetti",null,"Computational intelligence"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Computational Intelligence"]
[{"$nulls":4},"Artificial Intelligence"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Sommario/riassunto","This book presents advances in alternative swarm development that have proved to be effective in several complex problems. Swarm intelligence (SI) is a problem-solving methodology that results from the cooperation between a set of agents with similar characteristics. The study of biological entities, such as animals and insects, manifesting social behavior has resulted in several computational models of swarm intelligence. While there are numerous books addressing the most widely known swarm methods, namely ant colony algorithms and particle swarm optimization, those discussing new alternative approaches are rare. The focus on developments based on the simple modification of popular swarm methods overlooks the opportunity to discover new techniques and procedures that can be useful in solving problems formulated by the academic and industrial communities. Presenting various novel swarm methods and their practical applications, the book helps researchers, lecturers, engineersand practitioners solve their own optimization problems."]