David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Synthese 171 (1):111 - 133 (2009)
An agent often has a number of hypotheses, and must choose among them based on observations, or outcomes of experiments. Each of these observations can be viewed as providing evidence for or against various hypotheses. All the attempts to formalize this intuition up to now have assumed that associated with each hypothesis h there is a likelihood function μ h , which is a probability measure that intuitively describes how likely each observation is, conditional on h being the correct hypothesis. We consider an extension of this framework where there is uncertainty as to which of a number of likelihood functions is appropriate, and discuss how one formal approach to defining evidence, which views evidence as a function from priors to posteriors, can be generalized to accommodate this uncertainty.
|Keywords||Confirmation theory Weight of evidence Likelihood Uncertainty|
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References found in this work BETA
Henry Kyburg (1983). Recent Work in Inductive Logic. In Kenneth G. Lucey & Tibor R. Machan (eds.), American Philosophical Quarterly. Rowman & Allanheld 87--150.
Glenn Shafer (1976). A Mathematical Theory of Evidence. Princeton University Press.
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