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Efficiency and Effectiveness Metrics in Evolutionary Algorithms and Their Application Read chapter Read first chapter

2015 | OriginalPaper | Chapter

Multi AUV Intelligent Autonomous Learning Mechanism Based on QPSO Algorithm

Authors : Jian-Jun Li, Ru-Bo Zhang, Yu Yang

Published in: Intelligent Computing Theories and Methodologies

Publisher: Springer International Publishing

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Abstract

Intelligent autonomous learning is a hotspot of research on multi-agent system research, because of the PSO algorithm and multiple AUV system has loose coupling intelligent group structure, multiple AUV system flexibility and openness, multiple AUV system can be combined with swarm intelligence algorithm. So, using the swarm intelligence research of particle swarm optimization (pso) autonomous intelligent AUV underwater robot autonomous learning mechanism, can greatly improve the performance of many of AUV system. Quantum PSO algorithm and PSO algorithm based on the experimental verification, to prove QPSO algorithm has the certain superiority in the AUV more autonomous learning, in the process of each iteration self-learning optimal state, not only improve the efficiency of the algorithm, but also for the current to search for the optimal state, improve the accuracy of search algorithm.

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Metadata
Title
Multi AUV Intelligent Autonomous Learning Mechanism Based on QPSO Algorithm
Authors
Jian-Jun Li
Ru-Bo Zhang
Yu Yang
Copyright Year
2015
Book
Intelligent Computing Theories and Methodologies

Print ISBN: 978-3-319-22185-4

Electronic ISBN: 978-3-319-22186-1

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-22186-1_6

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