Abstract
Degrees of support and possibility are the central formal concepts in the theory of probabilistic argumentation (Haenni, 2005a, 2009; Haenni et al., 2000; Kohlas, 2003). This theory is driven by the general idea of putting forward the pros and cons of a proposition or hypothesis in question. The weights of the resulting logical arguments and counter-arguments are measured by probabilities, which are then turned into (sub-additive1) degrees of support and (super-additive) degrees of possibility.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Dempster, A. P. (1968). A generalization of Bayesian inference. Journal of the Royal Statistical Society, 30:205–247.
Haenni, R. (2005b). Using probabilistic argumentation for key validation in public-key cryptography. International Journal of Approximate Reasoning, 38(3):355–376.
Haenni, R. (2009). Probabilistic argumentation. Journal of Applied Logic, 7(2):155–176.
Haenni, R. and Hartmann, S. (2006). Modeling partially reliable information sources: a general approach based on Dempster-Shafer theory. International Journal of Information Fusion, 7(4):361–379.
Haenni, R., Kohlas, J., and Lehmann, N. (2000). Probabilistic argumentation systems. In Gabbay, D. M. and Smets, P., editors, Handbook of Defeasible Reasoning and Uncertainty Management Systems, volume 5: Algorithms for Uncertainty and Defeasible Reasoning, pages 221–288. Kluwer Academic Publishers, Dordrecht, Netherlands.
Haenni, R. and Lehmann, N. (2003). Probabilistic argumentation systems: a new perspective on Dempster-Shafer theory. International Journal of Intelligent Systems, Special Issue on the Dempster-Shafer Theory of Evidence, 18(1):93–106.
Haenni, R., Romeijn, J., Wheeler, G., and Williamson, J. (2008). Possible semantics for a common framework of probabilistic logics. In Huynh, V. N., editor, UncLog’08, International Workshop on Interval/Probabilistic Uncertainty and Non-Classical Logics, Advances in Soft Computing, Ishikawa, Japan.
Kohlas, J. (2003). Probabilistic argumentation systems: A new way to combine logic with probability. Journal of Applied Logic, 1(3–4):225–253.
Pearl, J. (1990a). Reasoning with belief functions: An analysis of compatibility. International Journal of Approximate Reasoning, 4(5–6):363–389.
Ruspini, E. H. (1986). The logical foundations of evidential reasoning. Technical Report 408, SRI International, AI Center, Menlo Park, USA.
Ruspini, E. H., Lowrance, J., and Strat, T. (1992). Understanding evidential reasoning. International Journal of Approximate Reasoning, 6(3):401–424.
Shafer, G. (1976). A Mathematical Theory of Evidence. Princeton University Press, Princeton, NJ.
Smets, P. and Kennes, R. (1994). The transferable belief model. Artificial Intelligence, 66:191–234.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2011 Springer Science+Business Media B.V.
About this chapter
Cite this chapter
Haenni, R., Romeijn, JW., Wheeler, G., Williamson, J. (2011). Probabilistic Argumentation. In: Probabilistic Logics and Probabilistic Networks. Synthese Library, vol 350. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0008-6_3
Download citation
DOI: https://doi.org/10.1007/978-94-007-0008-6_3
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-0007-9
Online ISBN: 978-94-007-0008-6
eBook Packages: Humanities, Social Sciences and LawPhilosophy and Religion (R0)