Dynamic Optimal Choice When Rewards are Unbounded Below
Theoretical Economics
2019-12-02 v1 Optimization and Control
Abstract
We propose a new approach to solving dynamic decision problems with rewards that are unbounded below. The approach involves transforming the Bellman equation in order to convert an unbounded problem into a bounded one. The major advantage is that, when the conditions stated below are satisfied, the transformed problem can be solved by iterating with a contraction mapping. While the method is not universal, we show by example that many common decision problems do satisfy our conditions.
Keywords
Cite
@article{arxiv.1911.13025,
title = {Dynamic Optimal Choice When Rewards are Unbounded Below},
author = {Qingyin Ma and John Stachurski},
journal= {arXiv preprint arXiv:1911.13025},
year = {2019}
}