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Multi-agent blackboard architecture for supporting legal decision making

Multi-agent blackboard architecture for supporting ...

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dc.contributor.author Szymański, Łukasz pl
dc.contributor.author Śnieżyński, Bartłomiej pl
dc.contributor.author Indurkhya, Bipin [SAP14011123] pl
dc.date.accessioned 2019-03-25T13:20:01Z
dc.date.available 2019-03-25T13:20:01Z
dc.date.issued 2018 pl
dc.identifier.issn 1508-2806 pl
dc.identifier.uri https://ruj.uj.edu.pl/xmlui/handle/item/71342
dc.language eng pl
dc.rights Udzielam licencji. Uznanie autorstwa 4.0 Międzynarodowa *
dc.rights.uri http://creativecommons.org/licenses/by/4.0/pl/legalcode *
dc.title Multi-agent blackboard architecture for supporting legal decision making pl
dc.type JournalArticle pl
dc.description.physical 457-477 pl
dc.description.additional Bibliogr. s. 474-477 pl
dc.identifier.weblink https://journals.agh.edu.pl/csci/article/view/3007 pl
dc.abstract.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 blackboard to store facts about current case. Knowledge is represented as a set of rules. Inference process is based on bottom-up control (forward chaining). The goal of our system is to find rationales for arguments supporting different decisions for a given case 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 effecive approach to model situations where a multitude of possibly conflicting factors must be taken into account in decision making. We briefly discuss two such scenarios: incorporating moral and ethical factors in decision making by autonomous systems (e.g. self-driven cars), and integrating eudaimonic (well-being) factors in modeling mobility patterns in a smart city. pl
dc.subject.en agent-based legal decision-making model pl
dc.subject.en blackboard architecture pl
dc.subject.en legal decision support pl
dc.description.volume 19 pl
dc.description.number 4 pl
dc.description.publication 1 pl
dc.identifier.doi 10.7494/csci.2018.19.4.3007 pl
dc.identifier.eissn 2300-7036 pl
dc.title.journal Computer Science pl
dc.language.container eng pl
dc.date.accession 2019-03-15 pl
dc.affiliation Wydział Filozoficzny : Instytut Filozofii pl
dc.subtype Article pl
dc.rights.original CC-BY; otwarte czasopismo; ostateczna wersja wydawcy; w momencie opublikowania; 0 pl
dc.identifier.project ROD UJ / OP pl
.pointsMNiSW [2018 B]: 12

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Udzielam licencji. Uznanie autorstwa 4.0 Międzynarodowa Except where otherwise noted, this item's license is described as Udzielam licencji. Uznanie autorstwa 4.0 Międzynarodowa