A hierarchical learning system incorporating with supervised, unsupervised and reinforcement learning

Jinglu Hu; Takafumi Sasakawa; Kotaro Hirasawa; Huiru Zheng

doi:10.1007/978-3-540-72383-7_48

A hierarchical learning system incorporating with supervised, unsupervised and reinforcement learning

Jinglu Hu^*, Takafumi Sasakawa, Kotaro Hirasawa, Huiru Zheng

^*Corresponding author for this work

Graduate School of Information, Production and Systems

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

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.

Original language	English
Title of host publication	Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings
Publisher	Springer Verlag
Pages	403-412
Number of pages	10
Edition	PART 1
ISBN (Print)	9783540723820
DOIs	https://doi.org/10.1007/978-3-540-72383-7_48
Publication status	Published - 2007
Event	4th International Symposium on Neural Networks, ISNN 2007 - Nanjing, China Duration: 2007 Jun 3 → 2007 Jun 7

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	4491 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	4th International Symposium on Neural Networks, ISNN 2007
Country/Territory	China
City	Nanjing
Period	07/6/3 → 07/6/7

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-540-72383-7_48

Cite this

Hu, J., Sasakawa, T., Hirasawa, K., & Zheng, H. (2007). A hierarchical learning system incorporating with supervised, unsupervised and reinforcement learning. In Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings (PART 1 ed., pp. 403-412). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4491 LNCS, No. PART 1). Springer Verlag. https://doi.org/10.1007/978-3-540-72383-7_48

A hierarchical learning system incorporating with supervised, unsupervised and reinforcement learning. / Hu, Jinglu; Sasakawa, Takafumi; Hirasawa, Kotaro; Zheng, Huiru.

Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 1. ed. Springer Verlag, 2007. p. 403-412 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4491 LNCS, No. PART 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Hu, J, Sasakawa, T, Hirasawa, K & Zheng, H 2007, A hierarchical learning system incorporating with supervised, unsupervised and reinforcement learning. in Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 4491 LNCS, Springer Verlag, pp. 403-412, 4th International Symposium on Neural Networks, ISNN 2007, Nanjing, China, 07/6/3. https://doi.org/10.1007/978-3-540-72383-7_48

Hu J, Sasakawa T, Hirasawa K, Zheng H. A hierarchical learning system incorporating with supervised, unsupervised and reinforcement learning. In Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 1 ed. Springer Verlag. 2007. p. 403-412. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). https://doi.org/10.1007/978-3-540-72383-7_48

Hu, Jinglu ; Sasakawa, Takafumi ; Hirasawa, Kotaro ; Zheng, Huiru. / A hierarchical learning system incorporating with supervised, unsupervised and reinforcement learning. Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 1. ed. Springer Verlag, 2007. pp. 403-412 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

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abstract = "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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A hierarchical learning system incorporating with supervised, unsupervised and reinforcement learning

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