Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/60114
Título: Success history applied to expert system for underwater glider path planning using differential evolution
Autores/as: Zamuda, Ales
Hernández Sosa, José Daniel 
Clasificación UNESCO: 120304 Inteligencia artificial
Palabras clave: Differential evolution
Linear population size reduction
Success-history based parameter adaptation
L-SHADE
Underwater glider path planning
Fecha de publicación: 2019
Proyectos: Cost Action Chipset 
Publicación seriada: Expert Systems with Applications 
Resumen: This paper presents an application of a recently well performing evolutionary algorithm for continuous numerical optimization, Success-History Based Adaptive Differential Evolution Algorithm (SHADE) including Linear population size reduction (L-SHADE), to an expert system for underwater glider path planning (UGPP). The proposed algorithm is compared to other similar algorithms and also to results from literature. The motivation of this work is to provide an alternative to the current glider mission control systems, that are based mostly on multidisciplinary human-expert teams from robotic and oceanographic areas. Initially configured as a decision-support expert system, the natural evolution of the tool is targeting higher autonomy levels.
URI: http://hdl.handle.net/10553/60114
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2018.10.048
Fuente: Expert Systems with Applications [ISSN 0957-4174], v. 119, p. 155-170, (Abril 2019)
Colección:Artículos
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