{"title":"通过计算理论连接大脑和机器人","authors":"D.M. Kawato","doi":"10.1109/ICNNB.2005.1614697","DOIUrl":null,"url":null,"abstract":"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","PeriodicalId":145719,"journal":{"name":"2005 International Conference on Neural Networks and Brain","volume":"91 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Connecting Brains and Robots by Computational Theories\",\"authors\":\"D.M. Kawato\",\"doi\":\"10.1109/ICNNB.2005.1614697\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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\",\"PeriodicalId\":145719,\"journal\":{\"name\":\"2005 International Conference on Neural Networks and Brain\",\"volume\":\"91 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-04-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2005 International Conference on Neural Networks and Brain\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNNB.2005.1614697\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 International Conference on Neural Networks and Brain","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNNB.2005.1614697","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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