Equal Weights, Flat Maxima, and Trivial Decisions.

Abstract

Most predictions are intended as a basis for decision making. The point of this paper is that prediction and decision require different methods. Equal weights, while often useful for prediction, are less useful for decision making. The action options available in any decision problem fall into three classes: sure winners, sure losers, and contenders. Sure winners and sure losers are defined by dominance, accepting sure winners and rejecting sure losers is trivial. Good decision rules should discriminate well among contenders. In the familiar pick-1 decision problem, options on the Pareto frontier (i.e. undominated options) almost always show negative correlations among attributes. Such negative correlations make equal weights inappropriate. This paper extends that result to the case in which a decision maker must pick k options out of n. In this case, the set of sure winners is usually not empty. It develops general procedures for identifying the set of contenders, given the options, k, and n. This set is a generalized Pareto frontier, of which the traditional kind is a special case. Simulations show that attribute intercorrelations among contenders are substantially depressed and typically negative, even if the intercorrelations in the whole set are positive. Such negative correlations among contenders strongly question the usefulness of equal weights for decision making.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1980
Accession Number
ADA138506

Entities

People

  • D. Von Winterfeldt
  • F. H. Barron
  • R. S. John
  • W. Brent Edwards

Organizations

  • University of Southern California

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  • Human Systems

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