DUGiDocsHybrid coordination of reinforcement learning-based behaviors for AUV control
dc.contributor.author
dc.date.accessioned
2010-05-04T12:57:13Z
dc.date.available
2010-05-03T15:06:18Z
2010-05-04T12:57:13Z
dc.date.issued
2001
dc.identifier.citation
Carreras Pérez, M. , Batlle i Grabulosa, J., i Ridao Rodríguez, P. (2001). Hybrid coordination of reinforcement learning-based behaviors for AUV control. IEEE/RSJ International Conference on Intelligent Robots and Systems : 2001 : Proceedings, 3, 1410-1415. Recuperat 04 maig 2010, a http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=977178
dc.identifier.isbn
0-7803-6612-3
dc.identifier.uri
dc.description.abstract
This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors
dc.format.mimetype
application/pdf
dc.language.iso
eng
dc.publisher
IEEE
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Reproducció digital del document publicat a: http://dx.doi.org/10.1109/IROS.2001.977178
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© IEEE/RSJ International Conference on Intelligent Robots and Systems : 2001 : Proceedings, vol. 3, p. 1410-1415
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Articles publicats (D-ATC)
dc.rights
Tots els drets reservats
dc.subject
dc.title
Hybrid coordination of reinforcement learning-based behaviors for AUV control
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/openAccess
dc.identifier.doi