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  • 标题:A Cognitive Model Based on Neuromodulated Plasticity
  • 本地全文:下载
  • 作者:Jing Huang ; Xiaogang Ruan ; Naigong Yu
  • 期刊名称:Computational Intelligence and Neuroscience
  • 印刷版ISSN:1687-5265
  • 电子版ISSN:1687-5273
  • 出版年度:2016
  • 卷号:2016
  • DOI:10.1155/2016/4296356
  • 出版社:Hindawi Publishing Corporation
  • 摘要:Associative learning, including classical conditioning and operant conditioning, is regarded as the most fundamental type of learning for animals and human beings. Many models have been proposed surrounding classical conditioning or operant conditioning. However, a unified and integrated model to explain the two types of conditioning is much less studied. Here, a model based on neuromodulated synaptic plasticity is presented. The model is bioinspired including multistored memory module and simulated VTA dopaminergic neurons to produce reward signal. The synaptic weights are modified according to the reward signal, which simulates the change of associative strengths in associative learning. The experiment results in real robots prove the suitability and validity of the proposed model.
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