Approximate Dynamic Programming via Iterated Bellman Inequalities

  title={Approximate Dynamic Programming via Iterated Bellman Inequalities},
  author={Yang Wang and Brendan O’Donoghue and Stephen Boyd},
In this paper we introduce new methods for finding functions that lower bound the value function of a stochastic control problem, using an iterated form of the Bellman inequality. Our method is based on solving linear or semidefinite programs, and produces both a bound on the optimal objective, as well as a suboptimal policy that appears to work very well. These results extend and improve bounds obtained in a previous paper using a single Bellman inequality condition. We describe the methods in… CONTINUE READING
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