Continuous-time Value Function Approximation in Reproducing Kernel Hilbert Spaces

Motoya Ohnishi, Masahiro Yukawa, Mikael Johansson, Masashi Sugiyama

Neural Information Processing Systems 

Motivated by the success of reinforcement learning (RL) for discrete-time tasks such as AlphaGo and Atari games, there has been a recent surge of interest in using RL for continuous-time control of physical systems (cf.

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