Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/60114
Title: Success history applied to expert system for underwater glider path planning using differential evolution
Authors: Zamuda, Ales
Hernández Sosa, José Daniel 
UNESCO Clasification: 120304 Inteligencia artificial
Keywords: Differential evolution
Linear population size reduction
Success-history based parameter adaptation
L-SHADE
Underwater glider path planning
Issue Date: 2019
Project: Cost Action Chipset 
Journal: Expert Systems with Applications 
Abstract: 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
Source: Expert Systems With Applications [ISSN 0957-4174], v. 119, p. 155-170
Appears in Collections:Artículos
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