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Resolution of Grue Using a Support Measure
Author(s) -
Raam Prabhakar Gokhale
Publication year - 2010
Publication title -
ssrn electronic journal
Language(s) - English
Resource type - Journals
ISSN - 1556-5068
DOI - 10.2139/ssrn.1776587
Subject(s) - measure (data warehouse) , resolution (logic) , computer science , data science , artificial intelligence , data mining
Goodman’s grue paradox is unassailable if we hold that instances confirm generalizations, for the evidence at hand is both an instance of ‘All emeralds are green’ and ‘All emeralds are grue’. But if we consider what bearing the denials of the two hypotheses have on the evidence, a very different picture emerges. This paper argues that the denial of ‘All emeralds are grue’ is more positively relevant to the evidence to date than the denial of ‘All emeralds are green’ is to the evidence and that therefore ‘All emeralds are green’ is better supported by the evidence than ‘All emeralds are grue’. The measure of support we employ—S(h|e) = p(e|h) – p(e|~h)—is motivated by the familiar relevance condition of confirmation, namely e confirms h only if p(h|e) > p(h).

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