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  • 标题:Reinforcement Learning based on Computational Cognitive Neuroscience in Neuromorphic VLSI Chips
  • 本地全文:下载
  • 作者:Mohammed Riyaz Ahmed ; Dr. B.K.Sujatha
  • 期刊名称:International Journal of Advanced Research In Computer Science and Software Engineering
  • 印刷版ISSN:2277-6451
  • 电子版ISSN:2277-128X
  • 出版年度:2013
  • 卷号:3
  • 期号:8
  • 出版社:S.S. Mishra
  • 摘要:Recent advances in study of Information Processing systems have developed in a number of interrelated, yet distinct disciplines which are developing overlapping domains of inquiry. Most of the attention, however is given to the Cognitive Sciences, which is the empirical study of intelligent systems, including humankind. Neuromorphic systems are inspired by the structure, function and plasticity of biological nervous systems. This field is evolving a new era in computing with a great promise for future medicine, healthcare delivery and industry. This paper focuses on the emerging trends in computational cognitive sciences by surveying on a new interdisciplinary field called neuromorphic engineering. A complete overview starting from its origin to its applications is described. The overall process of developing neural networks and simulation of them in a form of neuromorphic chip is explained. Modeling of Attention and Perception is done. Trivial Perception is modeled based on BDI models. In this paper, Cognitive models are used to implement the Reinforcement Learning in Neuromorphic VLSI Chips, to exhibit intelligence when the machines are exposed to an undefined Situation
  • 关键词:Computational Science; Cognitive Science; Neuroscience; Reinforcement Learning; Neuromorphic ;Engineering.
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