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Authors: Alejandro Agostini and Enric Celaya

Affiliation: Institut de Robòtica i Informática Industrial, Spain

Keyword(s): Robot Control, Reinforcement Learning, Categorization.

Related Ontology Subjects/Areas/Topics: Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Machine Learning in Control Applications

Abstract: Robotic applications often involve dealing with complex dynamic systems. In these cases coping with control requirements with conventional techniques is hard to achieve and a big effort has to be done in the design and tuning of the control system. An alternative to conventional control techniques is the use of automatic learning systems that could learn control policies automatically, by means of the experience. But the amount of experience required in complex problems is intractable unless some generalization is performed. Many learning techniques have been proposed to deal with this challenge but the applicability of them in a complex control task is still difficult because of their bad learning convergence or insufficient generalization. In this work a new learning technique, that exploits a kind of generalization called categorization, is used in a complex control task. The results obtained show that it is possible to learn, in short time and with good convergence, a control pol icy that outperforms a classical PID control tuned for the specific task of controlling a manipulator with high inertia and variable load. (More)

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Paper citation in several formats:
Agostini, A. and Celaya, E. (2005). FEASIBLE CONTROL OF COMPLEX SYSTEMS USING AUTOMATIC LEARNING. In Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO; ISBN 972-8865-29-5; ISSN 2184-2809, SciTePress, pages 284-287. DOI: 10.5220/0001174202840287

@conference{icinco05,
author={Alejandro Agostini. and Enric Celaya.},
title={FEASIBLE CONTROL OF COMPLEX SYSTEMS USING AUTOMATIC LEARNING},
booktitle={Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO},
year={2005},
pages={284-287},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001174202840287},
isbn={972-8865-29-5},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO
TI - FEASIBLE CONTROL OF COMPLEX SYSTEMS USING AUTOMATIC LEARNING
SN - 972-8865-29-5
IS - 2184-2809
AU - Agostini, A.
AU - Celaya, E.
PY - 2005
SP - 284
EP - 287
DO - 10.5220/0001174202840287
PB - SciTePress

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