On Compatibility between Situation Outcome Cases and Logical Cases

Case-based reasoning (CBR) is central to legal practice, relying on precedents to interpret and apply the law. Various formalisms have been proposed to represent cases, including cases represented as situation-outcome pairs (situation-outcome cases) and cases represented as logical formulas (logical cases). Connections between situation-outcome cases and logical cases have been preliminary explored, but interoperability between CBR models of these representations remains underexamined. To address this gap, this paper introduces four formal tools: (1) compatibility, which concerns interpolating a logical case into multiple situation-outcome cases; (2) enumerators, which generalise compatibility by interpolating logical case models into valid situation-outcome cases; (3) prototypers, which relate logical case models to reflexive and consistent situation-outcome CBR models, as illustrated by AA-CBR and the result model of precedential constraint; and (4) translators, which attempting the reverse, namely connecting such situation-outcome CBR models back to logical case models. Our investigation of these tools reveal how implicit cases can be introduced to simulate or align with another CBR model’s reasoning, which contributes to interoperability between CBR models.

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Publication Details

Published
2025-06-16
DOI
https://doi.org/10.1145/3769126.3769211
Primary Topic
Multi-Agent Systems and Negotiation
Type
article
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article

On Compatibility between Situation Outcome Cases and Logical Cases

Wachara Fungwacharakorn, Bart Verheij, Guilherme Paulino-Passos, Ken Satoh
Multi-Agent Systems and Negotiation
article

On Compatibility between Situation Outcome Cases and Logical Cases

Wachara Fungwacharakorn, Bart Verheij, Guilherme Paulino-Passos, Ken Satoh
article en

Abstract

Case-based reasoning (CBR) is central to legal practice, relying on precedents to interpret and apply the law. Various formalisms have been proposed to represent cases, including cases represented as situation-outcome pairs (situation-outcome cases) and cases represented as logical formulas (logical cases). Connections between situation-outcome cases and logical cases have been preliminary explored, but interoperability between CBR models of these representations remains underexamined. To address this gap, this paper introduces four formal tools: (1) compatibility, which concerns interpolating a logical case into multiple situation-outcome cases; (2) enumerators, which generalise compatibility by interpolating logical case models into valid situation-outcome cases; (3) prototypers, which relate logical case models to reflexive and consistent situation-outcome CBR models, as illustrated by AA-CBR and the result model of precedential constraint; and (4) translators, which attempting the reverse, namely connecting such situation-outcome CBR models back to logical case models. Our investigation of these tools reveal how implicit cases can be introduced to simulate or align with another CBR model’s reasoning, which contributes to interoperability between CBR models.

University of Groningen (NL), Thomson Reuters (United Kingdom) (GB), Research Organization of Information and Systems (JP)
Peace, Justice and strong institutions
Openalex Percentile: Top 17%
Multi-Agent Systems and Negotiation
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On Compatibility between Situation Outcome Cases and Logical Cases — Wachara Fungwacharakorn, Bart Verheij, et al. · (2025) | TGRS Research Map | TGRS