Multi-agent blackboard architecture for supporting legal decision making
| Autor: | Bipin Indurkhya, Bartlomiej Sniezynski, Lukasz Szymanski |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Computer Networks and Communications
Computer science Process (engineering) Inference agent-based legal decision-making model Blackboard system 050105 experimental psychology 060404 music Artificial Intelligence Statutory law Smart city Forward chaining legal decision support Computer Science (miscellaneous) 0501 psychology and cognitive sciences Set (psychology) 05 social sciences 06 humanities and the arts Blackboard (design pattern) Computer Graphics and Computer-Aided Design Data science Computational Theory and Mathematics Modeling and Simulation Computer Vision and Pattern Recognition blackboard architecture 0604 arts |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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