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Authors: Andreas Huemer 1 ; Mario Gongora 2 and David Elizondo 2

Affiliations: 1 Institute Of Creative Technologies, De Montfort University, United Kingdom ; 2 Centre for Computational Intelligence, De Montfort University, United Kingdom

Keyword(s): Spiking neural network, reinforcement learning, robot controller development.

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

Abstract: A novel methodology to create a powerful controller for robots that minimises the design effort is presented. We show that using the feedback from the robot itself, the system can learn from experience. A method is presented where the interpretation of the sensory feedback is integrated in the creation of the controller, which is achieved by growing a spiking neural network system. The feedback is extracted from a performance measuring function provided at the task definition stage, which takes into consideration the robot actions without the need for external or manual analysis.

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Paper citation in several formats:
Huemer, A.; Gongora, M. and Elizondo, D. (2008). SELF CONSTRUCTING NEURAL NETWORK ROBOT CONTROLLER BASED ON ON-LINE TASK PERFORMANCE FEEDBACK. In Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 978-989-8111-30-2; ISSN 2184-2809, SciTePress, pages 326-333. DOI: 10.5220/0001495503260333

@conference{icinco08,
author={Andreas Huemer. and Mario Gongora. and David Elizondo.},
title={SELF CONSTRUCTING NEURAL NETWORK ROBOT CONTROLLER BASED ON ON-LINE TASK PERFORMANCE FEEDBACK},
booktitle={Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2008},
pages={326-333},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001495503260333},
isbn={978-989-8111-30-2},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - SELF CONSTRUCTING NEURAL NETWORK ROBOT CONTROLLER BASED ON ON-LINE TASK PERFORMANCE FEEDBACK
SN - 978-989-8111-30-2
IS - 2184-2809
AU - Huemer, A.
AU - Gongora, M.
AU - Elizondo, D.
PY - 2008
SP - 326
EP - 333
DO - 10.5220/0001495503260333
PB - SciTePress