Case-Based Reasoning via Comparing the Strength Order of Features

Liuwen Yu, Dov Gabbay

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


Case-based reasoning (CBR) is broadly speaking a method of giving a verdict/decision on a new case query by comparing it with verdicts/decisions of known similar cases. Similarity of cases is determined either by best distance of the query case from the known cases and recently also using argumentation. The approach of this paper is not to rely on similarity or argumentation, but to use the entire set of known cases and their known verdicts to define the relative strength and importance of all the features involved in these cases. We then decide the verdict for the new case based on the strength of the features appearing in it.

Original languageEnglish
Title of host publicationExplainable and Transparent AI and Multi-Agent Systems - 4th International Workshop, EXTRAAMAS 2022, Revised Selected Papers
EditorsDavide Calvaresi, Amro Najjar, Michael Winikoff, Kary Främling
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages9
ISBN (Print)9783031155642
StatePublished - 2022
Externally publishedYes
Event4th International Workshop on Explainable and Transparent AI and Multi-Agent Systems, EXTRAAMAS 2022 - Virtual, Online
Duration: 9 May 202210 May 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13283 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference4th International Workshop on Explainable and Transparent AI and Multi-Agent Systems, EXTRAAMAS 2022
CityVirtual, Online

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.


  • Argumentation
  • Case-based reasoning
  • Legal reasoning
  • Strength of features


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