TY - GEN
T1 - A hierarchical learning system incorporating with supervised, unsupervised and reinforcement learning
AU - Hu, Jinglu
AU - Sasakawa, Takafumi
AU - Hirasawa, Kotaro
AU - Zheng, Huiru
PY - 2007
Y1 - 2007
N2 - According to Hebb's Cell assembly theory, the brain has the capability of function localization. On the other hand, it is suggested that the brain has three different learning paradigms: supervised, unsupervised and reinforcement learning. Inspired by the above knowledge of brain, we present a hierarchical learning system consisting of three parts: supervised learning (SL) part, unsupervised learning (UL) part and reinforcement learning (RL) part. The SL part is a main part learning input-output mapping; the UL part realizes the function localization of learning system by controlling firing strength of neurons in SL part based on input patterns; the RL part optimizes system performance by adjusting parameters in UL part. Simulation results confirm the effectiveness of the proposed hierarchical learning system.
AB - According to Hebb's Cell assembly theory, the brain has the capability of function localization. On the other hand, it is suggested that the brain has three different learning paradigms: supervised, unsupervised and reinforcement learning. Inspired by the above knowledge of brain, we present a hierarchical learning system consisting of three parts: supervised learning (SL) part, unsupervised learning (UL) part and reinforcement learning (RL) part. The SL part is a main part learning input-output mapping; the UL part realizes the function localization of learning system by controlling firing strength of neurons in SL part based on input patterns; the RL part optimizes system performance by adjusting parameters in UL part. Simulation results confirm the effectiveness of the proposed hierarchical learning system.
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U2 - 10.1007/978-3-540-72383-7_48
DO - 10.1007/978-3-540-72383-7_48
M3 - Conference contribution
AN - SCOPUS:37249062150
SN - 9783540723820
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 403
EP - 412
BT - Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings
PB - Springer Verlag
T2 - 4th International Symposium on Neural Networks, ISNN 2007
Y2 - 3 June 2007 through 7 June 2007
ER -