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Emergent Reasoning Structures in Law
Abstract
In modern legal systems, a large number of autonomous agents can achieve reasonably fair and accurate decisions in tens of thousands of legal cases. In many of those cases, the issues are complicated, the evidence is extensive, and the reasoning is complex. The decision-making process also integrates legal rules and policies with expert and non-expert evidence. This chapter discusses two major types of reasoning that have emerged to help bring about this remarkable social achievement: systems of rule-based deductions and patterns of evidence evaluation. In addition to those emergent structures, second-order reasoning about legal reasoning itself not only coordinates the decision-making, but also promotes the emergence of new reasoning structures. The chapter analyzes these types of reasoning structures using a many-valued, predicate, default logic – the Default-Logic (D-L) Framework. This framework is able to represent legal knowledge and reasoning in actual cases, to integrate and help evaluate expert and non-expert evidence, to coordinate agents working on different legal problems, and to guide the evolution of the knowledge model over time. The D-L Framework is also useful in automating portions of legal reasoning, as evidenced by the Legal Apprenticetm software. The framework therefore facilitates the interaction of human and non-human agents in legal decision- making, and makes it possible for non-human agents to participate in the evolution of legal reasoning in the future. Finally, because the D-L Framework itself is grounded in logic and not on theories peculiar to the legal domain, it is applicable to other knowledge domains that have a complexity similar to that of law and solve problems through default reasoning.
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