Skip to Main content Skip to Navigation
New interface
Preprints, Working Papers, ...

Diffusive limit approximation of pure jump optimal ergodic control problems

Abstract : Motivated by the design of fast reinforcement learning algorithms, we study the diffusive limit of a class of pure jump ergodic stochastic control problems. We show that, whenever the intensity of jumps is large enough, the approximation error is governed by the Hölder continuity of the Hessian matrix of the solution to the limit ergodic partial differential equation. This extends to this context the results of [1] obtained for finite horizon problems. We also explain how to construct a first order error correction term under appropriate smoothness assumptions. Finally, we quantify the error induced by the use of the Markov control policy constructed from the numerical finite difference scheme associated to the limit diffusive problem, this seems to be new in the literature and of its own interest. This approach permits to reduce very significantly the numerical resolution cost.
Document type :
Preprints, Working Papers, ...
Complete list of metadata
Contributor : Lorenzo Croissant Connect in order to contact the contributor
Submitted on : Thursday, September 29, 2022 - 5:45:55 PM
Last modification on : Saturday, October 1, 2022 - 3:46:42 AM


Files produced by the author(s)


  • HAL Id : hal-03792090, version 1
  • ARXIV : 2209.15284



Marc Abeille, Bruno Bouchard, Lorenzo Croissant. Diffusive limit approximation of pure jump optimal ergodic control problems. 2022. ⟨hal-03792090⟩



Record views


Files downloads