Skip to main content Accessibility help
×
Home

Probabilistic legal reasoning in CHRiSM

  • JON SNEYERS (a1), DANNY DE SCHREYE (a1) and THOM FRÜHWIRTH (a2)

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.

Copyright

References

Hide All
Dung, P. M. 1995. On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artificial Intelligence 77, 2, 321358.
Frühwirth, T. 2009. Constraint Handling Rules. Cambridge University Press.
Frühwirth, T. and Raiser, F., Eds. 2011. Constraint Handling Rules: Compilation, Execution, and Analysis. BOD.
Kakas, A. C., Kowalski, R. A. and Toni, F. 1992. Abductive logic programming. Journal of logic and computation 2, 6, 719770.
Kimmig, A., Demoen, B., De Raedt, L.et al., 2011. On the implementation of the probabilistic logic programming language ProbLog. TPLP 11, 2–3, 235262.
Nute, D. 2001. Defeasible logic: Theory, implementation, and applications. In Proceedings of 14th International Conference on Applications of Prolog (INAP 2001), 87–114.
Prakken, H. and Sartor, G. 1997. Argument-based extended logic programming with defeasible priorities. Journal of Applied Non-Classical Logics 7, 1, 2575.
Riveret, R., Rotolo, A., Sartor, G., Prakken, H. and Roth, B. 2007. Success chances in argument games: a probabilistic approach to legal disputes. In JURIX, Vol. 165, 99108.
Roth, B., Riveret, R., Rotolo, A. and Governatori, G. 2007. Strategic argumentation: a game theoretical investigation. In ICAIL. ACM, 8190.
Sato, T. 2008. A glimpse of symbolic-statistical modeling by PRISM. Journal of Intelligent Information Systems 31, 161176.
Sneyers, J., De Schreye, D. and Frühwirth, T. 2013. CHRiSM and probabilistic argumentation logic. In CHR 2013, 10th International Workshop on Constraint Handling Rules.
Sneyers, J., Meert, W., Vennekens, J., Kameya, Y. and Sato, T. 2010. CHR(PRISM)-based probabilistic logic learning. TPLP 10, 4–6, 433447.
Sneyers, J., Van Weert, P., Schrijvers, T. and De Koninck, L. 2010. As time goes by: Constraint Handling Rules. TPLP 10, 1, 147.
Vennekens, J., Verbaeten, S. and Bruynooghe, M. 2004. Logic programs with annotated disjunctions. In ICLP 2004, LNCS, vol. 3132. Springer, 431445.

Probabilistic legal reasoning in CHRiSM

  • JON SNEYERS (a1), DANNY DE SCHREYE (a1) and THOM FRÜHWIRTH (a2)

Metrics

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed