Document Type

Conference Paper

Rights

Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence

Disciplines

Computer Sciences, Bioinformatics

Publication Details

International Conference of the Italian Association for Artificial Intelligence

Abstract

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.

DOI

https://doi.org/10.1007/978-3-030-03840-3_15

Funder

Conselho Nacional de Desenvolvimento Científico e Tecnológico

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