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A behavior-based scheme using reinforcement learning for autonomous underwater vehicles

This paper presents a hybrid behavior-based scheme using reinforcement learning for high-level control of autonomous underwater vehicles (AUVs). Two main features of the presented approach are hybrid behavior coordination and semi on-line neural-Q_learning (SONQL). Hybrid behavior coordination takes advantages of robustness and modularity in the competitive approach as well as efficient trajectories in the cooperative approach. SONQL, a new continuous approach of the Q_learning algorithm with a multilayer neural network is used to learn behavior state/action mapping online. Experimental results show the feasibility of the presented approach for AUVs

© Oceanic Engineering, 2005, vol. 30, p. 416-427

IEEE

Author: Carreras Pérez, Marc
Yuh, Junku
Batlle i Grabulosa, Joan
Ridao Rodríguez, Pere
Date: 2005
Abstract: This paper presents a hybrid behavior-based scheme using reinforcement learning for high-level control of autonomous underwater vehicles (AUVs). Two main features of the presented approach are hybrid behavior coordination and semi on-line neural-Q_learning (SONQL). Hybrid behavior coordination takes advantages of robustness and modularity in the competitive approach as well as efficient trajectories in the cooperative approach. SONQL, a new continuous approach of the Q_learning algorithm with a multilayer neural network is used to learn behavior state/action mapping online. Experimental results show the feasibility of the presented approach for AUVs
Format: application/pdf
Citation: Carreras, M., Yuh, J., Batlle, J., i Ridao, P. (2005). A behavior-based scheme using reinforcement learning for autonomous underwater vehicles. IEEE Journal of Oceanic Engineering, 30, 2, 416-427. Recuperat 05 maig 2010, a http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1522520
ISSN: 0364-9059
Document access: http://hdl.handle.net/10256/2169
Language: eng
Publisher: IEEE
Collection: Reproducció digital del document publicat a: http://dx.doi.org/10.1109/JOE.2004.835805
Articles publicats (D-ATC)
Is part of: © Oceanic Engineering, 2005, vol. 30, p. 416-427
Rights: Tots els drets reservats
Subject: Algorismes computacionals
Aprenentatge per reforç
Intel·ligència artificial
Robots autònoms
Xarxes neuronals (Informàtica)
Vehicles submergibles
Artificial intelligence
Autonomous robots
Computer algorithms
Neural networks (Computer science)
Reinforcement learning
Submersibles
Title: A behavior-based scheme using reinforcement learning for autonomous underwater vehicles
Type: info:eu-repo/semantics/article
Repository: DUGiDocs

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