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Towards Cardinality-Aware Evidential Combination Rules in Dempster–Shafer Theory

  • 13-07-2024
  • Technical Contribution

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Abstract

The article delves into the limitations of Dempster’s rule in Dempster–Shafer Theory (DST), a framework widely used in AI for handling uncertainty. It introduces cardinality-aware combination rules, which consider the cardinality of focal set elements to improve decision-making. These rules address the counterintuitive results of Dempster’s rule and offer a more nuanced approach to evidence combination. The paper categorizes these rules into three classes and presents case studies to evaluate their performance. It also highlights the importance of incorporating cardinality in the combination process to enhance AI systems' performance in uncertain environments. The findings suggest that cardinality-aware rules can overcome the limitations of Dempster’s rule, but further research is needed to manage both consensus and conflict redistribution effectively.

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Title
Towards Cardinality-Aware Evidential Combination Rules in Dempster–Shafer Theory
Authors
Faouzi Sebbak
Mustapha Reda Senouci
Farid Benhammadi
M’hamed Mataoui
Walid Cherifi
Publication date
13-07-2024
Publisher
Springer Berlin Heidelberg
Published in
KI - Künstliche Intelligenz
Print ISSN: 0933-1875
Electronic ISSN: 1610-1987
DOI
https://doi.org/10.1007/s13218-024-00859-4
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