David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jonathan Jenkins Ichikawa
Jack Alan Reynolds
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Journal for the Theory of Social Behaviour 41 (2):209-227 (2011)
Most decisions in life involve ambiguity, where probabilities can not be meaningfully specified, as much as they involve probabilistic uncertainty. In such conditions, the aspiration to utility maximization may be self-deceptive. We propose “robust satisficing” as an alternative to utility maximizing as the normative standard for rational decision making in such circumstances. Instead of seeking to maximize the expected value, or utility, of a decision outcome, robust satisficing aims to maximize the robustness to uncertainty of a satisfactory outcome. That is, robust satisficing asks, “what is a ‘good enough’ outcome,” and then seeks the option that will produce such an outcome under the widest set of circumstances. We explore the conditions under which robust satisficing is a more appropriate norm for decision making than utility maximizing.
|Keywords||utility maximizing radical uncertainty probabilistic uncertainty psychological satisficing robust satisficing|
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Leonard J. Savage (1954). The Foundations of Statistics. Wiley Publications in Statistics.
John Locke (1700). An Essay Concerning Human Understanding. Oxford University Press.
Frank Knight (1921). Risk, Uncertainty and Profit. University of Chicago Press.
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