Abstract
In this paper, we present a decision support system for lawyers. This system is built upon an argumentation framework for decision making. A logic language is used as a concrete data structure for holding the statements like knowledge, goals, and decisions. Different priorities are attached to these items corresponding to the uncertainty of the knowledge about the circumstances, the lawyer’s preferences, and the expected utilities of sentences. These concrete data structures consist of information providing the backbone of arguments. Due to the abductive nature of practical reasoning, arguments are built by reasoning backwards, and possibly by making suppositions over missing information. Moreover, arguments are defined as tree-like structures. In this way, our computer system, implemented in Prolog, suggests some actions and provides an interactive and intelligible explanation of this solution.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Prakken, H., Sartor, G.: The role of logic in computational models of legal argument: a critical survey. In: Kakas, A.C., Sadri, F. (eds.) Computational Logic: Logic Programming and Beyond. LNCS (LNAI), vol. 2408, pp. 343–380. Springer, Heidelberg (2002)
Bench-Capon, T., Prakken, H.: Justifying actions by accruing arguments. In: Proc. of the 1st International Conference on Computational Models of Argument, pp. 247–258. IOS Press, Amsterdam (2006)
Clemen, R.T.: Making Hard Decisions. Duxbury Press (1996)
Amgoud, L., Cayrol, C.: A reasoning model based on the production of acceptable arguments. Annals of Maths and AI 34(1-3), 197–215 (2002)
Schweimeier, R., Schroeder, M.: Notions of attack and justified arguments for extended logic programs. In: van Harmelen, F. (ed.) Proc. of the 15th European Conference on Artificial Intelligence (ECAI), pp. 536–540. IOS Press, Amsterdam (2002)
Vreeswijk, G.: Abstract argumentation systems. Artificial Intelligence 90(1-2), 225–279 (1997)
Dung, P.M.: On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artificial Intelligence 77(2), 321–357 (1995)
Dung, P.M., Mancarella, P., Toni, F.: Computing ideal sceptical argumentation. Artificial Intelligence, Special Issue on Argumentation in Artificial Intelligence 171(10-15), 642–674 (2007)
Vreeswijk, G., Prakken, H.: Credulous and sceptical argument games for preferred semantics. In: Brewka, G., Moniz Pereira, L., Ojeda-Aciego, M., de Guzmán, I.P. (eds.) JELIA 2000. LNCS (LNAI), vol. 1919, pp. 239–253. Springer, Heidelberg (2000)
Gartner, D., Toni, F.: CaSAPI: a system for credulous and sceptical argumentation. In: Simari, G., Torroni, P. (eds.) Proc. of Workshop on Argumentation for Non-monotonic Reasoning, pp. 80–95 (2007)
Dung, P.M., Kowalski, R.A., Toni, F.: Dialectic proof procedures for assumption-based, admissible argumentation. Artificial Intelligence 170(2), 114–159 (2006)
Fox, J., Parsons, S.: On using arguments for reasoning about actions and values. In: Doyle, J., Thomason, R.H. (eds.) Proceedings of the Working Papers of the AAAI Spring Symposium on Qualitative Preferences in Deliberation and Practical Reasoning, pp. 55–63. Standford, Menlo Park (1997)
Oliver, R.M., Smith, J.Q.: Influence Diagrams, Belief Nets and Decision Analysis. John Wiley and Sons, Chichester (1988)
Raz, J. (ed.): Practical Reasoning. Oxford University Press, Oxford (1978)
Leila Amgoud, S.K.: On the generation of bipolar goals in argumentation-based negotiation. In: Rahwan, I., Moraïtis, P., Reed, C. (eds.) ArgMAS 2004. LNCS (LNAI), vol. 3366, pp. 192–207. Springer, Heidelberg (2005)
Thomason, R.H.: Desires and defaults: A framework for planning with inferred goals. In: Proc. of the seventh International Confenrence on Principle of Knowledge Representation and Reasoning (KR), pp. 702–713 (2000)
Hulstijn, J., van der Torre, L.W.N.: Combining goal generation and planning in an argumentation framework. In: Proc. of the 9h International Workshop on Non-Monotonic Reasoning (NMR), pp. 212–218 (2004)
Rahwan, I., Amgoud, L.: An argumentation-based approach for practical reasoning. In: Proc. of the 5th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS), Hakodate, Japan, pp. 347–354. ACM Press, New York (2006)
Guillermo, R., Simari, A.J., García, M.C.: Actions, planning and defeasible reasoning. In: Proc. of the 10th International Workshop on Non-Monotonic Reasoning (NMR), Whistler BC, Canada, pp. 377–384 (2004)
Kakas, A., Moraitis, P.: Argumentative-based decision-making for autonomous agents. In: Proceedings of the 2nd International Joint Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), pp. 883–890. ACM Press, New York (2003)
Atkinson, K., Bench-Capon, T., McBurney, P.: Computational representation of practical argument. Synthese, special issue on Knowledge, Rationality and Action 152(2), 157–206 (2006)
Ouerdane, W., Maudet, N., Tsoukias, A.: Arguing over actions that involve multiple criteria: A critical review. In: Mellouli, K. (ed.) ECSQARU 2007. LNCS (LNAI), vol. 4724, pp. 308–319. Springer, Heidelberg (2007)
Amgoud, L., Prade, H.: Comparing decisions in an argumentation-based setting. In: Proc. of the 11th International Workshop on Non-Monotonic Reasoning (NMR), Session on Argumentation, Dialogue, and Decision Making, Lake District, UK, pp. 426–432 (2006)
Amgoud, L., Prade, H.: Explaining qualitative decision under uncertainty by argumentation. In: Proc. of the 21st National Conference on Artificial Intelligence (AAAI), Boston, pp. 16–20 (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Morge, M. (2008). Computing Argumentation for Decision Making in Legal Disputes. In: Casanovas, P., Sartor, G., Casellas, N., Rubino, R. (eds) Computable Models of the Law. Lecture Notes in Computer Science(), vol 4884. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85569-9_13
Download citation
DOI: https://doi.org/10.1007/978-3-540-85569-9_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85568-2
Online ISBN: 978-3-540-85569-9
eBook Packages: Computer ScienceComputer Science (R0)