Robust estimation and control under commitment
成果类型:
Article
署名作者:
Hansen, LP; Sargent, TJ
署名单位:
New York University; University of Chicago
刊物名称:
JOURNAL OF ECONOMIC THEORY
ISSN/ISSBN:
0022-0531
DOI:
10.1016/j.jet.2005.06.006
发表日期:
2005
页码:
258-301
关键词:
Learning
model uncertainty
Bayes' law
entropy
Robustness
risk-sensitivity
COMMITMENT
time inconsistency
摘要:
In a Markov decision problem with hidden state variables, a decision maker expresses fear that his model is misspecified by surrounding it with a set of alternatives that are nearby as measured by their expected log likelihood ratios (entropies). Sets of martingales represent alternative models. Within a two-player zero-sum game under commitment, a minimizing player chooses a martingale at time 0. Probability distributions that solve distorted filtering problems serve as state variables, much like the posterior in problems without concerns about misspecification. We state conditions under which an equilibrium of the zero-sum game with commitment has a recursive representation that can be cast in terms of two risk-sensitivity operators. We apply our results to a linear quadratic example that makes contact with findings of T. Basar and P. Bernhard [H-infinity-Optimal Control and Related Minimax Design Problems, second ed., Birkhauser, Basel, 1995] and P. Whittle [Risk-sensitive Optimal Control, Wiley, New York, 1990]. (c) 2005 Published by Elsevier Inc.