Mobile robots can benefit from machine learning approaches for improving their behaviors in performing complex activities. In recent years, these techniques have been used to find optimal parameter sets for many behaviors. In particular, layered learning has been proposed to improve learning rate in robot learning tasks. In this paper, we consider a layered learning approach for learning optimal parameters of basic control routines, behaviours and strategy selection. We compare three different methods in the different layers: genetic algorithm, Nelder-Mead, and policy gradient. Moreover, we study how to use a 3D simulator for speeding up robot learning. The results of our experimental work on AIBO robots are useful not only to state differences and similarities between different robot learning approaches used within the layered learning framework, but also to evaluate a more effective learning methodology that makes use of a simulator. © 2008 Springer-Verlag Berlin Heidelberg.

Layered learning for a soccer legged robot helped with a 3D simulator / Andrea, Cherubini; F., Giannone; Iocchi, Luca. - 5001 LNAI:(2008), pp. 385-392. (Intervento presentato al convegno 11th RoboCup International Symposium, RoboCup 2007 tenutosi a Atlanta; United States nel 9 July 2007 through 10 July 2007) [10.1007/978-3-540-68847-1_39].

Layered learning for a soccer legged robot helped with a 3D simulator

IOCCHI, Luca
2008

Abstract

Mobile robots can benefit from machine learning approaches for improving their behaviors in performing complex activities. In recent years, these techniques have been used to find optimal parameter sets for many behaviors. In particular, layered learning has been proposed to improve learning rate in robot learning tasks. In this paper, we consider a layered learning approach for learning optimal parameters of basic control routines, behaviours and strategy selection. We compare three different methods in the different layers: genetic algorithm, Nelder-Mead, and policy gradient. Moreover, we study how to use a 3D simulator for speeding up robot learning. The results of our experimental work on AIBO robots are useful not only to state differences and similarities between different robot learning approaches used within the layered learning framework, but also to evaluate a more effective learning methodology that makes use of a simulator. © 2008 Springer-Verlag Berlin Heidelberg.
2008
11th RoboCup International Symposium, RoboCup 2007
Effective learning; International symposium; Layered learning
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Layered learning for a soccer legged robot helped with a 3D simulator / Andrea, Cherubini; F., Giannone; Iocchi, Luca. - 5001 LNAI:(2008), pp. 385-392. (Intervento presentato al convegno 11th RoboCup International Symposium, RoboCup 2007 tenutosi a Atlanta; United States nel 9 July 2007 through 10 July 2007) [10.1007/978-3-540-68847-1_39].
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