TY - JOUR T1 - Towards interactive explanation-based nutrition virtual coaching systems A1 - Buzcu, Berk A1 - Tessa, Melissa A1 - Tchappi, Igor A1 - Najjar, Amro A1 - Hulstijn, Joris A1 - Calvaresi, Davide A1 - Aydoğan, Reyhan JA - Autonomous Agents and Multi-Agent Systems Y1 - 2024 UR - https://link.springer.com/article/10.1007/s10458-023-09634-5 M2 - doi: 10.1007/s10458-023-09634-5 KW - Explainable AI KW - Interactive KW - Nutrition virtual coach KW - recommender systems N2 - The awareness about healthy lifestyles is increasing, opening to personalized intelligent health coaching applications. A demand for more than mere suggestions and mechanistic interactions has driven attention to nutrition virtual coaching systems (NVC) as a bridge between human--machine interaction and recommender, informative, persuasive, and argumentation systems. NVC can rely on data-driven opaque mechanisms. Therefore, it is crucial to enable NVC to explain their doing (i.e., engaging the user in discussions (via arguments) about dietary solutions/alternatives). By doing so, transparency, user acceptance, and engagement are expected to be boosted. This study focuses on NVC agents generating personalized food recommendations based on user-specific factors such as allergies, eating habits, lifestyles, and ingredient preferences. In particular, we propose a user-agent negotiation process entailing run-time feedback mechanisms to react to both recommendations and related explanations. Lastly, the study presents the findings obtained by the experiments conducted with multi-background participants to evaluate the acceptability and effectiveness of the proposed system. The results indicate that most participants value the opportunity to provide feedback and receive explanations for recommendations. Additionally, the users are fond of receiving information tailored to their needs. Furthermore, our interactive recommendation system performed better than the corresponding traditional recommendation system in terms of effectiveness regarding the number of agreements and rounds. ER -