TY - GEN
T1 - A neural framework for robot motor learning based on memory consolidation
AU - Ben Amor, Heni
AU - Ikemoto, Shuhei
AU - Minato, Takashi
AU - Jung, Bernhard
AU - Ishiguro, Hiroshi
N1 - Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2007
Y1 - 2007
N2 - Neural networks are a popular technique for learning the adaptive control of non-linear plants. When applied to the complex control of android robots, however, they suffer from serious limitations such as the moving target problem, i.e. the interference between old and newly learned knowledge. However, in order to achieve lifelong learning, it is important that robots are able to acquire new motor skills without for-getting previously learned ones. To overcome these problems, we propose a new framework for motor learning, which is based on consolidation. The framework contains a new rehearsal algorithm for retaining previously acquired knowledge and a growing neural network. In experiments, the framework was successfully applied to an artifical benchmark problem and a real-world android robot.
AB - Neural networks are a popular technique for learning the adaptive control of non-linear plants. When applied to the complex control of android robots, however, they suffer from serious limitations such as the moving target problem, i.e. the interference between old and newly learned knowledge. However, in order to achieve lifelong learning, it is important that robots are able to acquire new motor skills without for-getting previously learned ones. To overcome these problems, we propose a new framework for motor learning, which is based on consolidation. The framework contains a new rehearsal algorithm for retaining previously acquired knowledge and a growing neural network. In experiments, the framework was successfully applied to an artifical benchmark problem and a real-world android robot.
UR - http://www.scopus.com/inward/record.url?scp=38049092662&partnerID=8YFLogxK
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U2 - 10.1007/978-3-540-71629-7_72
DO - 10.1007/978-3-540-71629-7_72
M3 - Conference contribution
AN - SCOPUS:38049092662
SN - 9783540715900
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 641
EP - 648
BT - Adaptive and Natural Computing Algorithms - 8th International Conference, ICANNGA 2007, Proceedings
PB - Springer Verlag
T2 - 8th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2007
Y2 - 11 April 2007 through 14 April 2007
ER -