We use approximate dynamic programming for stor- age (ADPS) to blend reinforcement learning and math programming. We simulate only T time periods in advance and ...
A new method, approximate dynamic programming for storage, to solve storage problems with continuous, convex decision sets, that allows math programming to ...
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The paper has two main features. Firstly, an approximate solution is found using characteristics of the optimal solution determined by dynamic programming.
This paper presents a new method, approximate dynamic programming for storage, to solve storage problems with continuous, convex decision sets. Unlike other ...
We present and benchmark an approximate dynamic programming algorithm that is capable of designing near- optimal control policies for time-dependent, ...
This paper presents a new method, approximate dynamic programming for storage, to solve storage problems with continuous, convex decision sets. Unlike other ...
This paper reports on the performance of a variety of ap- proximation methods that have been developed in the approx- imate dynamic programming community, ...
Approximate Dynamic Programming (ADP) is a powerful technique to solve large scale discrete time multistage stochastic control processes, i.e., ...
Jul 10, 2013 · Abstract: We prove convergence of an approximate dynamic programming algorithm for a class of high-dimensional stochastic control problems ...
Approximate Dynamic Programming simplifies large-scale optimization problems using value function approximations and policy approximations.