General Representation of Epistemically Optimal Procedures

Abstract

Assuming that votes are independent, the epistemically optimal procedure in a binary collective choice problem is known to be a weighted supermajority rule with weights given by personal log likelihood ratios. It is shown here that an analogous result holds in a much more general model. Firstly, the result follows from a more basic principle than expected-utility maximisation, namely from an axiom (“Epistemic Monotonicity”) which requires neither utilities nor prior probabilities of the ‘correctness’ of alternatives. Secondly, a person’s input need not be a vote for an alternative; it may be any type of input, for instance a subjective degree of belief or probability of the correctness of one of the alternatives. The case of a profile of subjective degrees of belief is particularly appealing, since no parameters such as competence parameters need to be known here.

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Correspondence to Franz Dietrich.

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Dietrich, F. General Representation of Epistemically Optimal Procedures. Soc Choice Welfare 26, 263–283 (2006). https://doi.org/10.1007/s00355-006-0094-2

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Keywords

  • Prior Probability
  • Utility Maximisation
  • Subjective Probability
  • Weighted Rule
  • Correct Alternative