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Analogical Reasoning, Generalization, and Rule Learning for Common Law Reasoning

Published: 07 September 2023 Publication History

Abstract

Research in AI & Law has sought to model common-law case-based reasoning by creating analogies from cases, extracting and applying rules from cases, or both. This paper presents a new approach to extracting legal information from cases and several methods to apply it to new cases, including by analogy and by conversion to logical rules. It evaluates the approaches on a dataset of real-world cases and compares the results to off-the-shelf machine-learning techniques. We conclude that abstract legal information can be extracted from similar cases through analogical generalization, and that the extracted legal schemas can be used to reason about and solve other cases both by analogy and by rules.

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  • (2024)AI, Law and beyond. A transdisciplinary ecosystem for the future of AI & LawArtificial Intelligence and Law10.1007/s10506-024-09404-yOnline publication date: 16-May-2024

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  1. Analogical Reasoning, Generalization, and Rule Learning for Common Law Reasoning

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      ICAIL '23: Proceedings of the Nineteenth International Conference on Artificial Intelligence and Law
      June 2023
      499 pages
      ISBN:9798400701979
      DOI:10.1145/3594536
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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      New York, NY, United States

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      Published: 07 September 2023

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      Author Tags

      1. Analogy
      2. Legal Schemas
      3. Precedential Reasoning
      4. Rule Learning

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      • Research-article
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      • Refereed limited

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      • Computational Cognition and Machine Intelligence Program of the Air Force Office of Scientific Research

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      ICAIL 2023
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      Overall Acceptance Rate 69 of 169 submissions, 41%

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      • (2024)AI, Law and beyond. A transdisciplinary ecosystem for the future of AI & LawArtificial Intelligence and Law10.1007/s10506-024-09404-yOnline publication date: 16-May-2024

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