• DOI:10.1007/978-3-662-43505-2_3
• Corpus ID: 11737662

Possibility Theory and Its Applications: Where Do We Stand?

@inproceedings{Dubois2015PossibilityTA,
  title={Possibility Theory and Its Applications: Where Do We Stand?},
  author={Didier Dubois and Henri Prade},
  booktitle={Handbook of Computational Intelligence},
  year={2015}
}

• D. Dubois, H. Prade
• Published in
  Handbook of Computational…
  2015
• Computer Science

This chapter provides an overview of possibility theory, emphasizing its historical roots and its recent developments. Possibility theory lies at the crossroads between fuzzy sets, probability, and nonmonotonic reasoning. Possibility theory can be cast either in an ordinal or in a numerical setting. Qualitative possibility theory is closely related to belief revision theory, and commonsense reasoning with exception-tainted knowledge in artificial intelligence. Possibilistic logic provides a rich representation setting, which enables the handling of lower bounds of possibility theory measures, while remaining close to classical logic. Qualitative possibility theory has been axiomatically justified in a decision-theoretic framework in the style of Savage, thus providing a foundation for qualitative decision theory. Quantitative possibility theory is the simplest framework for statistical reasoning with imprecise probabilities. As such, it has close connections with random set theory and confidence intervals, and can provide a tool for uncertainty propagation with limited statistical or subjective information.