An artificial intelligence-based approach to deal with argumentation applied to food quality in a public health policy
Argumentation 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 Dungs 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 stakeholders argumentation by targeting some specific audiences.
artificial intelligence argumentation decision support arbitration benefit-risk analysis preferences knowledge representation case study nutrition