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Probabilistic legal reasoning in CHRiSM

Published online by Cambridge University Press:  25 September 2013

JON SNEYERS ,
DANNY DE SCHREYE  and
THOM FRÜHWIRTH
JON SNEYERS
Affiliation:
Department of Computer Science, KU Leuven, Belgium (e-mail: FirstName.LastName@cs.kuleuven.be)
DANNY DE SCHREYE
Affiliation:
Department of Computer Science, KU Leuven, Belgium (e-mail: FirstName.LastName@cs.kuleuven.be)
THOM FRÜHWIRTH
Affiliation:
University of Ulm, Germany (e-mail: thom.fruehwirth@uni-ulm.de)
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Abstract

Riveret et al. have proposed a framework for probabilistic legal reasoning. Their goal is to determine the chance of winning a court case, given the probabilities of the judge accepting certain claimed facts and legal rules.

In this paper we tackle the same problem by defining and implementing a new formalism, called probabilistic argumentation logic, which can be seen as a probabilistic generalization of Nute's defeasible logic. Not only does this provide an automation of the — only hand-performed — computations in Riveret et al, it also provides a solution to one of their open problems: a method to determine the initial probabilities from a given body of precedents.

Type
Regular Papers
Information
Theory and Practice of Logic Programming , Volume 13 , Special Issue 4-5: 29th International Conference on Logic Programming , July 2013 , pp. 769 - 781
Copyright
Copyright © 2013 [JON SNEYERS, DANNY DE SCHREYE and THOM FRÜHWIRTH] 

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