Multi-agent blackboard architecture for supporting legal decision making

• Autorzy: Szymański Ł. , Śnieżyński B. , Indurkhya B.

Identyfikatory

DOI

10.7494/csci.2018.19.4.3007

• Języki publikacji: EN

Abstrakty

EN

Our research objective is to design a system to support legal decision making using the multi-agent blackboard architecture. Agents represent experts that may apply various knowledge-processing algorithms and knowledge sources. Experts cooperate with each other using the blackboard to store facts about a current case. Knowledge is represented as a set of rules. The inference process is based on bottom-up control (forward chaining). The goal of our system is to find rationales for arguments that support different decisions for a given case by using precedents and statutory knowledge. Our system also uses top- -down knowledge from statutes and precedents to interactively query the user for additional facts when such facts could affect the judgment. The rationales for various judgments are presented to the user, who may choose the most appropriate one. We present two example scenarios in Polish traffic law to illustrate the features of our system. Based on these results, we argue that the blackboard architecture provides an effective approach to modeling situations where a multitude of possibly conflicting factors must be taken into account in the decision making.

Słowa kluczowe

EN

agent-based legal decision-making model; blackboard architecture; legal decision support

• Wydawca: Wydawnictwa AGH
• Czasopismo: Computer Science
• Rocznik: 2018
• Tom: Vol. 19 (4)
• Strony: 457–--477
• Opis fizyczny: Bibliogr, 33 poz., rys.

Twórcy

autor

Szymański Ł.

• AGH University of Science and Technology, Krakow, Poland

autor

Śnieżyński B.

• AGH University of Science and Technology, Faculty of Computer Science, Electronics and Telecommunications, Krakow, Poland

autor

Indurkhya B.

• AGH University of Science and Technology, Krakow, Poland

Bibliografia

• [1] Aamodt A., Plaza E.: Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches, IOS Press, vol. 7(1), pp. 39–59, 1994.
• [2] Arcia A., Suero-Tejeda N., Bales M.E., Merrill J.A., Yoon S., Woollen J., Bakken S.: Sometimes more is more: iterative participatory design of infographics for engagement of community members with varying levels of health literacy, Journal of the American Medical Informatics Association, vol. 23(1), pp. 174–183, 2016. https://doi.org/10.1093/jamia/ocv079.
• [3] Ashley K.D.: An Approach to Legal Ontologies: the Case-Based Reasoning Perspective, Jurix 2008 Workshop on Approaches to Legal Ontologies, ITTIG-CNR, EUI, Florence, Italy December, 2008. http://www.lrdc.pitt.edu/Ashley/Ont ologiesTalk2Final.pdf.
• [4] Atkinson K., Bench-Capon T.: Legal case-based reasoning as practical reasoning, Artificial Intelligence and Law, vol. 13(1), pp. 93–131, 2005. https://doi.org/ 10.1007/s10506-006-9003-3.
• [5] Bartels B.L.: Top-Down and Bottom-Up Models of Judicial Reasoning. In: Klein D., Mitchell G. (eds.), The Psychology of Judicial Decision Making, Oxford University Press, pp. 41–55, 2010. https://doi.org/10.1093/acprof: oso/9780195367584.003.0003.
• [6] Bench-Capon T., Prakken H., Sartor G.: Argumentation in Legal Reasoning. In: Simari G., Rahwan I. (eds.), Argumentation in Artificial Intelligence, Springer, Boston, MA 2009, pp. 363–382. https://doi.org/10.1007/978-0-387-98197- 018.
• [7] Branting L.K.: Building explanations from rules and structured cases, International Journal of Man-Machine Studies, vol. 34(6), pp. 797–837, 1991. https: //doi.org/10.1016/0020-7373(91)90012-V.
• [8] Carver N., Lesser V.: The Evolution of Blackboard Control Architectures. Technical Report, University of Massachusetts Amherst, MA, USA, 1992.
• [9] Cohen J.: Blindfolds Off: Judges on How They Decide. American Bar Association, 2014.
• [10] Cooper A., Reimann R., Cronin D., Noessel C.: About Face: The Essentials of Interaction Design. Wiley Publishing, 4th ed., 2014.
• [11] Corkill D.D.: Blackboard Systems, AI Expert, vol. 6(9), pp. 40–47, 1991.
• [12] De Waal A.W., Indurkhya B., Vanderschuren M.: Re-interpreting motility constructs within a Mobility as a Service framing, the case of eudaimonic and hedonic well-being. In: Proceedings of the T2M Conference, Montreal, 24–27 October 2018.
• [13] Erman L.D., Hayes-Roth F., Lesser V.R., Reddy D.R.: The Hearsay-II Speech- Understanding System: Integrating Knowledge to Resolve Uncertainty, ACM Computing Surveys (CSUR), vol. 12(2), pp. 213–253, 1980. https://doi.org/ 10.1145/356810.356816
• [14] v.d.L. Gardner A.: Rules and Cases for Legal Reasoning: Notes on Some Neglected Aspects. In: AAAI Technical Report SS-98-04, pp. 64–68, 1998. https:// www.aaai.org/Papers/Symposia/Spring/1998/SS-98-04/SS98-04-012.pdf.
• [15] Guarino N.: Formal ontology and information systems. In: Formal Ontology in Information Systems: Proceedings of the First International Conference (FOIS’98), June 6-8, Trento, Italy, pp. 3–15. 1998.
• [16] Healy T.: The Great Dissent: How Oliver Wendell Holmes Changed His Mind and Changed the History of Free Speech in America. Metropolitan Books, New York, 2013.
• [17] Indurkhya B.: Using set-of-support control strategy to deal with indeterminacy in legal reasoning. In: van Kralingen R..W., van den Herik H.J., Prins J.E.J., Sergot M., Zeleznikow J. (eds.), Legal Knowledge Based Systems (Jurix’96), pp. 123–133, Tilburg University Press, The Netherlands, 1996.
• [18] Indurkhya B.: On modeling creativity in legal reasoning. In: ICAIL’97 Proceedings of the 6th international conference on Artificial intelligence and law, Melbourne, Australia, June 30 – July 03, 1997, pp. 180–189, 1997. https: //doi.org/10.1145/261618.261651.
• [19] Indurkhya B., Misztal-Radecka J.: On Modeling Cognitive and Affective Factors in Legal Decision-Making. In: Rotolo A. (ed.), Legal knowledge and information systems: JURIX’2015: the twenty-eight annual conference, pp. 157–160, IOS Press, Amsterdam, 2015.
• [20] Indurkhya B., Misztal-Radecka J.: Incorporating Human Dimension in Autonomous Decision-Making on Moral and Ethical Issues. In: Proceedings of the AAAI Spring Symposium on Ethical and Moral Considerations in Non-Human Agents. Palo Alto: California, pp. 226–230, 2016.
• [21] Misztal J., Indurkhya B.: A Blackboard System for Generating Poetry, Computer Science, vol. 17(2), pp. 265–294, 2015.
• [22] Misztal J., Indurkhya B.: Explaining Contextual Recommendations: Interaction Design Study and Prototype Implementation. In: O’Donovan J., Felfernig A., Tintarev N., Brusilovsky P., Semeraro G., Lops P.: Proceedings of the Joint Workshop on Interfaces and Human Decision Making for Recommender Systems, IntRS 2015, co-located with ACM Conference on Recommender Systems (RecSys 2015), Vienna, Austria, September 19, 2015. pp. 13–20, 2015.
• [23] Oskamp A., Walker R.F., Schrickx J.A., van den Berg P.H.: PROLEXS divide and rule: a legal application. In: ICAIL ’89 Proceedings of the 2nd international conference on Artificial intelligence and law, pp. 54–62. ACM, New York, NY, USA, 1989. https://doi.org/10.1145/74014.74022.
• [24] Posner R.A.: How Judges Think. Harvard University Press, Cambridge (MA), 2010.
• [25] Robbennlot J.K., MacCoun R.J., Darley J.M.: Multiple constraint satisfaction in judging. In: Klein D.E., Mitchell G. (eds.), The Psychology of Judicial Decision Making. Oxford University Press, 2010.
• [26] Schweizer M.D.: Kognitive Täuschungen vor Gericht: eine empirische Studie, Dissertation der Rechtswissenschaftlichen Fakultät der Universität Zürich, 2005.
• [27] Shortliffe E.: Computer-based medical consultations: MYCIN, Elsevier 1976.
• [28] Simonsen J., Hertzum M.: Sustained Participatory Design: Extending the Iterative Approach, Design Issues, vol. 28(3), pp. 10–21, 2012. https://doi.org/10 .1162/DESIa00158.
• [29] Skalak D.B., Rissland E.L.: Arguments and cases: An inevitable intertwining, Artificial Intelligence and Law, vol. 1(1), pp. 3–44, 1992.
• [30] Sniezynski B., Legien G., Wilk-Kołodziejczyk D., Kluska-Nawarecka S., Nawarecki E., Jaskowiec K.: Creative Expert System: Comparison of Proof Searching Strategies. In: Nguyen N.T., Tojo S., Nguyen L.M., Trawinski B. (eds.), Intelligent Information and Database Systems, pp. 400–409. Springer International Publishing, Cham, 2017.
• [31] Twining W., Miers D.: How To Do Things With Rules: A Primer of Interpretation (2nd ed.). Weidenfeld and Nicolson, London, 1982.
• [32] Vidmar N.: The psychology of Trial Judging, Current Directions in Psychological Science, vol. 20(1), pp. 58–62, 2011. https://doi.org/10.1177%2F0963721410 397283.
• [33] Wisdom J.: Gods, Proceedings of the Aristotelian Society, vol. 45, pp. 185–206, 1944.