A Comparative Study of Defeasible Argumentation and Non-monotonic Fuzzy Reasoning for Elderly Survival Prediction Using Biomarkers

  • Lucas RizzoEmail author
  • Ljiljana Majnaric
  • Luca Longo
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11298)


Computational argumentation has been gaining momentum as a solid theoretical research discipline for inference under uncertainty with incomplete and contradicting knowledge. However, its practical counterpart is underdeveloped, with a lack of studies focused on the investigation of its impact in real-world settings and with real knowledge. In this study, computational argumentation is compared against non-monotonic fuzzy reasoning and evaluated in the domain of biological markers for the prediction of mortality in an elderly population. Different non-monotonic argument-based models and fuzzy reasoning models have been designed using an extensive knowledge base gathered from an expert in the field. An analysis of the true positive and false positive rate of the inferences of such models has been performed. Findings indicate a superior inferential capacity of the designed argument-based models.


Argumentation Theory Non-monotonic reasoning Defeasible reasoning Fuzzy reasoning Possibility Theory Biomarkers 



Lucas Middeldorf Rizzo would like to thank CNPq (Conselho Nacional de Desenvolvimento Científico e Tecnológico) for his Science Without Borders scholarship, proc n. 232822/2014-0.


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Authors and Affiliations

  1. 1.School of ComputingDublin Institute of TechnologyDublinIreland
  2. 2.Department of Family Medicine, School of MedicineUniversity of OsijekOsijekCroatia

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