Suppr超能文献

脉冲神经元群体中的强化学习。

Reinforcement learning in populations of spiking neurons.

作者信息

Urbanczik Robert, Senn Walter

机构信息

Department of Physiology, University of Bern, Bühlplatz 5, CH-3012 Bern, Switzerland.

出版信息

Nat Neurosci. 2009 Mar;12(3):250-2. doi: 10.1038/nn.2264. Epub 2009 Feb 15.

Abstract

Population coding is widely regarded as an important mechanism for achieving reliable behavioral responses despite neuronal variability. However, standard reinforcement learning slows down with increasing population size, as the global reward signal becomes less and less related to the performance of any single neuron. We found that learning speeds up with increasing population size if, in addition to global reward, feedback about the population response modulates synaptic plasticity.

摘要

群体编码被广泛认为是一种重要机制,可实现可靠的行为反应,尽管神经元存在变异性。然而,随着群体规模的增加,标准强化学习会变慢,因为全局奖励信号与任何单个神经元的表现越来越不相关。我们发现,如果除了全局奖励之外,关于群体反应的反馈还能调节突触可塑性,那么学习速度会随着群体规模的增加而加快。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验