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Reinforcement learning in continuous-time and space
Cagatay Yildiz

Sat Jul 23 06:40 AM -- 07:20 AM (PDT) @

In this talk, we will introduce a continuous-time reinforcement learning (CTRL) framework. Our talk starts with a categorization of RL problems and naturally motivates a continuous-time perspective to RL. We then introduce a model-based CTRL approach, which solves physical control tasks using neural ordinary differential equations as a sub-routine. We conclude by briefly introducing recent approaches to CTRL.

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Cagatay Yildiz (University of Tuebingen)

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