Evolutionary Optimization of Echo State Networks: Multiple Motor Pattern Learning
André Frank Krause, Volker Dürr, Bettina Bläsing, Thomas Schack
2010
Abstract
Echo State Networks are a special class of recurrent neural networks, that are well suited for attractor-based learning of motor patterns. Using structural multi-objective optimization, the trade-off between network size and accuracy can be identified. This allows to choose a feasible model capacity for a follow-up full-weight optimization. Both optimization steps can be combined into a nested, hierarchical optimization procedure. It is shown to produce small and efficient networks, that are capable of storing multiple motor patterns in a single net. Especially the smaller networks can interpolate between learned patterns using bifurcation inputs.
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in Harvard Style
Frank Krause A., Dürr V., Bläsing B. and Schack T. (2010). Evolutionary Optimization of Echo State Networks: Multiple Motor Pattern Learning . In Proceedings of the 6th International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: Workshop ANNIIP, (ICINCO 2010) ISBN 978-989-8425-03-4, pages 63-71. DOI: 10.5220/0003027500630071
in Bibtex Style
@conference{workshop anniip10,
author={André Frank Krause and Volker Dürr and Bettina Bläsing and Thomas Schack},
title={Evolutionary Optimization of Echo State Networks: Multiple Motor Pattern Learning},
booktitle={Proceedings of the 6th International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: Workshop ANNIIP, (ICINCO 2010)},
year={2010},
pages={63-71},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003027500630071},
isbn={978-989-8425-03-4},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 6th International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: Workshop ANNIIP, (ICINCO 2010)
TI - Evolutionary Optimization of Echo State Networks: Multiple Motor Pattern Learning
SN - 978-989-8425-03-4
AU - Frank Krause A.
AU - Dürr V.
AU - Bläsing B.
AU - Schack T.
PY - 2010
SP - 63
EP - 71
DO - 10.5220/0003027500630071