Temporal-Difference Learning - An Online Support Vector Regression Approach

Hugo Tanzarella Teixeira, Celso Pascoli Bottura

Abstract

This paper proposes a new algorithm for Temporal-Difference (TD) learning using online support vector regression. It benefits from the good generalization properties support vector regression (SVR) has, and also can do incremental learning and automatically track variation of environment with time-varying characteristics. Using the online SVR we can obtain good estimation of value function in TD learning in linear and nonlinear prediction problems. Experimental results demonstrate the effectiveness of the proposed method by comparison with others methods.

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Paper Citation


in Harvard Style

Tanzarella Teixeira H. and Pascoli Bottura C. (2015). Temporal-Difference Learning - An Online Support Vector Regression Approach . In Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-122-9, pages 318-323. DOI: 10.5220/0005572103180323


in Bibtex Style

@conference{icinco15,
author={Hugo Tanzarella Teixeira and Celso Pascoli Bottura},
title={Temporal-Difference Learning - An Online Support Vector Regression Approach},
booktitle={Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2015},
pages={318-323},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005572103180323},
isbn={978-989-758-122-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Temporal-Difference Learning - An Online Support Vector Regression Approach
SN - 978-989-758-122-9
AU - Tanzarella Teixeira H.
AU - Pascoli Bottura C.
PY - 2015
SP - 318
EP - 323
DO - 10.5220/0005572103180323