Berlin / Moscow / Cambridge / Bamberg / Providence / London / New York / /
Company
Princeton University Press / MIT Press / John Wiley and Sons / John Wiley & Sons / /
Country
Germany / U.S.S.R. / / /
Facility
Middlesex University / /
IndustryTerm
binary and uncountable utilities / optimisation systems / free energy / inner product / adaptive and learning systems / learning systems / exploration algorithms / online learning systems / online learning algorithms / physical systems / feasible solutions / /
Organization
Middlesex University / London / School of Engineering and Information Sciences / American Mathematical Society / MIT / Princeton University / Society for Industrial and Applied Mathematics / USSR Academy of Sciences / /
Person
Roman V. Belavkin / L. S. Pontryagin / V / /
Position
author / /
ProvinceOrState
Kentucky / /
PublishedMedium
Machine Learning / Physical Review / Journal of Artificial Intelligence Research / /
In IEEE International Symposium on Adaptive Dynamic Programming and Reinforcement Learning, [removed]Bounds of Optimal Learning Roman V. Belavkin Abstract—Learning is considered as a dynamic process described by a trajec