Contractivity of Bellman Operator in Risk Averse Dynamic Programming with Infinite Horizon
Optimization and Control
2022-08-04 v1 Applications
Abstract
The paper deals with a risk averse dynamic programming problem with infinite horizon. First, the required assumptions are formulated to have the problem well defined. Then the Bellman equation is derived, which may be also seen as a standalone reinforcement learning problem. The fact that the Bellman operator is contraction is proved, guaranteeing convergence of various solution algorithms used for dynamic programming as well as reinforcement learning problems, which we demonstrate on the value iteration algorithm.
Keywords
Cite
@article{arxiv.2208.01990,
title = {Contractivity of Bellman Operator in Risk Averse Dynamic Programming with Infinite Horizon},
author = {Martin Šmíd and Miloš Kopa},
journal= {arXiv preprint arXiv:2208.01990},
year = {2022}
}