通过计算理论连接大脑和机器人

D.M. Kawato
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引用次数: 0

摘要

在ATR计算神经科学实验室,神经生理学和机器人研究探索了几个关键概念,如小脑内部模型、多内部模型、马赛克、模仿学习、生物动机机器人两足运动、模块化和分层强化学习模型。ATR CNS实验室最近的研究成果包括基于计算模型的成像、fMRI-MEG组合中的分层变分贝叶斯方法和机器人实验,这些都可能成为神经科学新方法的基础
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Connecting Brains and Robots by Computational Theories
In ATR Computational Neuroscience Laboratories neurophysiological and robotics studies explored several key concepts such as cerebellar internal models, multiple internal models, MOSAIC, imitation learning, biologically motivated robot biped locomotion, modular and hierarchical reinforcement learning models. Recent efforts in ATR CNS labs including computational-model based imaging, hierarchical variational Bayesian method in fMRI-MEG combination, and robotics experiments could be the bases of the new methodology in neuroscience
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