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An artificial intelligence-based approach to deal with argumentation applied to food quality in a public health policy

By Jean-Rémi Bourguet, Rallou Thomopoulos, Marie-Laure Mugnier and Joel Abecassis

Abstract

International audienceArgumentation is a relatively new research area in Artificial Intelligence. Since the early 1980s, its use has been investigated in various frameworks. We propose a general model for recommendation-based argumentation by extending Dung's seminal argumentation system. This approach is applied to analyse argumentation on food quality in a public health policy. Cereal products, and more specifically bread, are used by decision makers as a healthy lever to fight against diseases such as obesity or diabetes. Our model outputs new recommendations based on stakeholder's argumentation by targeting some specific audiences

Topics: benefit-risk analysis, arbitration, artificial intelligence, argumentation, decision support, case study, nutrition, knowledge representation, preferences, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Publisher: 'Elsevier BV'
Year: 2013
DOI identifier: 10.1016/j.eswa.2013.01.059
OAI identifier: oai:HAL:lirmm-00835177v1
Provided by: HAL-CIRAD
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