Robust dynamic programming
成果类型：
Article
署名作者：
Iyengar, GN
署名单位：
Columbia University
刊物名称：
MATHEMATICS OF OPERATIONS RESEARCH
ISSN/ISSBN：
0364-765X
DOI：
10.1287/moor.1040.0129
发表日期：
2005
页码：
257-280
关键词：
摘要：
In this paper we propose a robust formulation for discrete time dynamic programming (DP). The objective of the robust formulation is to systematically mitigate the sensitivity of the DP optimal policy to ambiguity in the underlying transition probabilities. The ambiguity is modeled by associating a set of conditional measures with each state-action pair. Consequently, in the robust formulation each policy has a set of measures associated with it. We prove that when this set of measures has a certain rectangularity property, all of the main results for finite and infinite horizon DP extend to natural robust counterparts. We discuss techniques from Nilim and El Ghaoui [17] for constructing suitable sets of conditional measures that allow one to efficiently solve for the optimal robust policy. We also show that robust DP is equivalent to stochastic zero-sum games with perfect information.
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