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Applied mathematics / Robot control / Computational neuroscience / Humanoid robot / Inverse dynamics / ICub / Machine learning / Simulation / Algorithm / Cybernetics / Science / Robotics


Incremental learning of context-dependent dynamic internal models for robot control Lorenzo Jamone1 , Bruno Damas1,2 , Jos´e Santos-Victor1 Abstract— Accurate dynamic models can be very difficult to compute analytical
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Document Date: 2014-11-26 09:15:07

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City

Santos / /

Company

Prentice-Hall / IMLE / Neural Networks / Autonomous Systems / /

Country

Portugal / /

Facility

Prentice Hall / Hall International Eds / /

IndustryTerm

recent incremental learning algorithm / least-squares algorithm / probabilistic algorithm / bank / online stream / online learning / recent online learning algorithm / regression algorithms / Online Algorithm / energy efficiency / online learning algorithm / online adaptation / online estimation / iCub software developers / learning algorithm / /

Organization

Instituto Superior T´ecnico / European Union / Instituto de Sistemas / Universidade de Lisboa / /

Person

A. Bernardino / J. Santos-Victor / N. Endo / B. Damas / M. Lopes / L. Jamone / F. Janabi-Sharifi / V / C. von Hofsten / A. Takanishi / K. Rosander / L.Montesano / /

Position

Multiple paired forward / dynamic model for control leads / controller / learned model to control the system / /

ProgrammingLanguage

R / /

PublishedMedium

Journal of Neuroscience / /

Technology

Neuroscience / learning algorithm / recent online learning algorithm / recent incremental learning algorithm / online learning algorithm / On-line regression algorithms / machine learning / simulation / least-squares algorithm / EM algorithm / probabilistic algorithm / CAD / /

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