Judicial Support Tool: Finding the k Most Likely Judicial Worlds

Maksim Bolonkin, Sayak Chakrabarty, Cristian Molinaro*, V. S. Subrahmanian

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Judges sometimes make mistakes. We propose JUST, a logical framework within which judges can record propositions about a case and witness statements where a witness says that certain propositions are true or false. JUST allows the judge (or a jury) to assign a rating of credibility to witness statements. A world is an assignment of true/false to each proposition, which is required to satisfy case-specific integrity constraints. We first develop JUST ’s explicit algorithm, which calculates the k most likely worlds without using independence assumptions between propositions. The judge may use these calculated top-k most likely worlds to make her final decision. For this computation, JUST  uses a suite of “combination” functions. We also develop JUST ’s implicit algorithm, which is far more efficient. We test JUST on 5 real-world court cases and 19 TV court cases, showing that JUST works well in practice.

Original languageEnglish (US)
Title of host publicationScalable Uncertainty Management - 16th International Conference, SUM 2024, Proceedings
EditorsSébastien Destercke, Maria Vanina Martinez, Giuseppe Sanfilippo
PublisherSpringer Science and Business Media Deutschland GmbH
Pages53-69
Number of pages17
ISBN (Print)9783031762345
DOIs
StatePublished - 2025
Event16th International Conference on Scalable Uncertainty Management, SUM 2024 - Palermo, Italy
Duration: Nov 27 2024Nov 29 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume15350 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Scalable Uncertainty Management, SUM 2024
Country/TerritoryItaly
CityPalermo
Period11/27/2411/29/24

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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