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Author:

Zuo, GY (Zuo, GY.) (Scholars:左国玉) | Yang, BB (Yang, BB.) | Ruan, XG (Ruan, XG.)

Indexed by:

CPCI-S SCIE

Abstract:

A spiking-neuron based cognitive model with classical conditioning behaviors is proposed. With a reflex arc structure and a reinforcement learning method based on the Hebb rule, the cognitive model possesses the property of 'stimulate-response-reinforcement' and can simulate the learning process of classical conditioning. An experiment on the inverted pendulum validated that this model can learn the balance control strategy by classical conditioning.

Keyword:

Author Community:

  • [ 1 ] Beijing Univ Technol, Inst Artificial Intelligence & Robot, Beijing 100022, Peoples R China

Reprint Author's Address:

  • 左国玉

    [Zuo, GY]Beijing Univ Technol, Inst Artificial Intelligence & Robot, Beijing 100022, Peoples R China

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Source :

ADVANCES IN INTELLIGENT COMPUTING, PT 2, PROCEEDINGS

ISSN: 0302-9743

Year: 2005

Volume: 3645

Page: 939-948

JCR Journal Grade:4

Cited Count:

WoS CC Cited Count: 1

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 10

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