Info-Gap Robust-Satisficing and the Probability of Survival
AbstractIn this paper we study why, and when, and in what form, a satisficing strategy is a better bet for survival, than a strategy which uses the best available information in attempting to optimize the outcome. We prove that, under severe uncertainty, a robust-satisficing decision has a better probability of survival than a best-model outcome-optimizing decision. These results are based on non-probabilistic info-gap decision theory, which provides a quantification of Knightian uncertainty. We show that our results are applicable to Bayesian mixing of two models, allocation between a risky and a risk-free asset, foraging behavior, explaining Ellsberg's `paradox', satisfying multiple requirements, forecasting in dynamical systems, and managing exogenous uncertainties.
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Bibliographic InfoPaper provided by Netherlands Central Bank, Research Department in its series DNB Working Papers with number 138.
Date of creation: Apr 2007
Date of revision:
Satisficing; bounded rationality; Knightian uncertainty; robustness; probability of sur-vival; info-gap theory.;
Find related papers by JEL classification:
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-04-28 (All new papers)
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