Dynamic Optimal Choice When Rewards are Unbounded Below

Qingyin Ma; John Stachurski

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arXiv · 1911.13025

Dynamic Optimal Choice When Rewards are Unbounded Below

Qingyin Ma·John Stachurski

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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.

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Qingyin Ma, John Stachurski. 2019-11-29. Dynamic Optimal Choice When Rewards are Unbounded Below. https://arxiv.org/abs/1911.13025

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