The main aim of the present work is to establish connections between the theory of dynamic programming and the statistical decision theory. The paper deals with a nonMarkovian dynamic programming ...

We introduce a novel approach to solving dynamic programming problems, such as those in many economic models, on a quantum annealer, a specialized device that performs combinatorial optimization.

This course covers reinforcement learning aka dynamic programming, which is a modeling principle capturing dynamic environments and stochastic nature of events. The main goal is to learn dynamic ...

This is a preview. Log in through your library . Abstract A dynamic decision problem in which the effect of control action is either delayed for a number of time periods or has an effect that lasts ...

Learning how to predict future events from patterns of past events is a critical challenge in the field of artificial intelligence. As machine learning pioneer Yann LeCun writes, “prediction is the ...