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Strict Uncertainty: A Criterion for Moderately Pessimistic Decision Makers *
Author(s) -
Ballestero Enrique
Publication year - 2002
Publication title -
decision sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.238
H-Index - 108
eISSN - 1540-5915
pISSN - 0011-7315
DOI - 10.1111/j.1540-5915.2002.tb01637.x
Subject(s) - disappointment , ranking (information retrieval) , mathematics , pessimism , minimax , mathematical economics , axiom , rank (graph theory) , outcome (game theory) , decision rule , set (abstract data type) , meaning (existential) , computer science , statistics , artificial intelligence , social psychology , combinatorics , psychology , epistemology , philosophy , geometry , psychotherapist , programming language
This paper proposes a decision rule to rank actions under strict uncertainty, the available information being limited to the states of nature, the set of alternative rows, and the consequence of choosing every row if a given state occurs. This rule is suitable to moderately pessimistic individuals and social groups, these agents being neither maximax nor maximin decision makers but people who assume that the best outcome from the action will not occur. For these decision makers the paper shows the existence of a consistent weight system in which one and only one weight is attached to each state of the world under plausible conditions of domination. Most of the traditional axioms are satisfied by the proposed ranking approach. In the frame of disappointment (measured by ranges of column dispersion), the meaning of some controversial postulates used in the literature is explained. The proposed criterion is a departure from Laplace's (1825) rule and from the remaining standard criteria. Only in the special case of equal column dispersion do both Laplace's rule and the proposed weights lead to the same solution.