Abstract
People’s awareness about the importance of healthy lifestyles is rising. This opens new possibilities for personalized intelligent health and coaching applications. In particular, there is a need for more than simple recommendations and mechanistic interactions. Recent studies have identified nutrition virtual coaching systems (NVC) as a technological solution, possibly bridging technologies such as recommender, informative, persuasive, and argumentation systems. Enabling NVC to explain recommendations and discuss (argument) dietary solutions and alternative items or behaviors is crucial to improve the transparency of these applications and enhance user acceptability and retain their engagement. This study primarily focuses on virtual agents personalizing the generation of food recipes recommendation according to users’ allergies, eating habits, lifestyles, nutritional values, etc. Although the agent would nudge the user to consume healthier food, users may tend to object in favor of tastier food. To resolve this divergence, we propose a user-agent negotiation interacting over the revision of the recommendation (via feedback and explanations) or convincing (via explainable arguments) the user of its benefits and importance. Finally, the paper presents our initial findings on the acceptability and usability of such a system obtained via tests with real users. Our preliminary experimental results show that the majority of the participants appreciate the ability to express their feedback as well as receive explanations of the recommendations, while there is still room for improvement in the persuasiveness of the explanations.
Supported by Chist-Era (grant CHIST-ERA-19-XAI-005).
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Notes
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The details of the utility calculation are explained below.
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We would like to state that the experiment protocol adopted in this study was approved by the Ethics Committee of Özyeğin university, and informed consent was obtained from all participants.
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Acknowledgments
This work has been par ally supported by the Chist-Era grant CHIST-ERA-19-XAI-005, and by (i) the Swiss National Science Foundation (G.A. 20CH21_195530), (ii) the Italian Ministry for Universities and Research, (iii) the Luxembourg National Research Fund (G.A. INTER/CHIST/19/14589586), (iv) the Scientific and Research Council of Turkey (TÜBİTAK, G.A. 120N680).
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Buzcu, B., Varadhajaran, V., Tchappi, I., Najjar, A., Calvaresi, D., Aydoğan, R. (2023). Explanation-Based Negotiation Protocol for Nutrition Virtual Coaching. In: Aydoğan, R., Criado, N., Lang, J., Sanchez-Anguix, V., Serramia, M. (eds) PRIMA 2022: Principles and Practice of Multi-Agent Systems. PRIMA 2022. Lecture Notes in Computer Science(), vol 13753. Springer, Cham. https://doi.org/10.1007/978-3-031-21203-1_2
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