Abstract
Dynamic uncertain inference is the formation of opinions based upon evidence or argument whose availability is neither disclosed to the analyst in advance nor disclosed all at once. Normative accounts of belief change, which work well when the analyst has prior notice of well-designed experiments and their possible outcomes, may not be applicable to less tidy occasions of inference. In addition, there is the clerical challenge of keeping track of what has been observed, what relates to what, and how. This Article begins with a discussion of subjective valuation in general. An approach to deliberation, similar to what is practiced in the multiattribute utility modeling community, is then suggested for dynamic credibility assessment. Features of the proposed technique are explained through their application to a celebrated French murder investigation. The method presented here may be reconciled with Bayesian belief models by noting that the latter lack a consensus view of how stable beliefs form in the first place. Thus, the ideas discussed here may be taken as an account of original belief formation, and so complementary rather than antagonistic to subjective probability methods.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Physica-Verlag Heidelberg
About this chapter
Cite this chapter
Snow, P., Belis, M. (2002). Structured Deliberation for Dynamic Uncertain Inference. In: MacCrimmon, M., Tillers, P. (eds) The Dynamics of Judicial Proof. Studies in Fuzziness and Soft Computing, vol 94. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1792-8_20
Download citation
DOI: https://doi.org/10.1007/978-3-7908-1792-8_20
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-662-00323-7
Online ISBN: 978-3-7908-1792-8
eBook Packages: Springer Book Archive