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A hybrid, auto-adaptive, and rule-based multi-agent approach using evolutionary algorithms for improved searching

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A hybrid, auto-adaptive, and rule-based multi-agent approach using evolutionary algorithms for improved searching

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Izquierdo Sebastián, J.; Montalvo Arango, I.; Campbell, E.; Pérez García, R. (2015). A hybrid, auto-adaptive, and rule-based multi-agent approach using evolutionary algorithms for improved searching. Engineering Optimization. 1-13. doi:10.1080/0305215X.2015.1107434

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/64597

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Title: A hybrid, auto-adaptive, and rule-based multi-agent approach using evolutionary algorithms for improved searching
Author:
UPV Unit: Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada
Universitat Politècnica de València. Departamento de Ingeniería Hidráulica y Medio Ambiente - Departament d'Enginyeria Hidràulica i Medi Ambient
Issued date:
Abstract:
Selecting the most appropriate heuristic for solving a specific problem is not easy, for many reasons. This article focuses on one of these reasons: traditionally, the solution search process has operated in a given manner ...[+]
Subjects: Evolutionary optimization , Data Mining , Rule extraction
Copyrigths: Reserva de todos los derechos
Source:
Engineering Optimization. (issn: 0305-215X )
DOI: 10.1080/0305215X.2015.1107434
Publisher:
Taylor & Francis: STM, Behavioural Science and Public Health Titles
Publisher version: http://dx.doi.org/10.1080/0305215X.2015.1107434
Type: Artículo

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