{"type":"ScholarlyArticle","title":"Keeping People Active and Healthy at Home Using a Reinforcement Learning-based Fitness Recommendation Framework","authors":[{"name":"Elias Tragos","slug":"elias-tragos","given":"Elias","family":"Tragos","affiliation":"Insight Centre for Data Analytics , University College Dublin"},{"name":"Diarmuid O'Reilly-Morgan","slug":"diarmuid-o-reilly-morgan","given":"Diarmuid","family":"O'Reilly-Morgan","affiliation":"Insight Centre for Data Analytics , University College Dublin"},{"name":"James Geraci","slug":"james-geraci","given":"James","family":"Geraci","affiliation":"Samsung Electronics Co., Ltd. , Seoul , Republic of Korea"},{"name":"Bichen Shi","slug":"bichen-shi","given":"Bichen","family":"Shi","affiliation":"Insight Centre for Data Analytics , University College Dublin"},{"name":"Barry Smyth","slug":"barry-smyth","given":"Barry","family":"Smyth","affiliation":"Insight Centre for Data Analytics , University College Dublin"},{"name":"Cailbhe Doherty","slug":"cailbhe-doherty","given":"Cailbhe","family":"Doherty","affiliation":"Insight Centre for Data Analytics , University College Dublin; School of Public Health, Physiotherapy and Sports Science , University College Dublin ,"},{"name":"Aonghus Lawlor","slug":"aonghus-lawlor","given":"Aonghus","family":"Lawlor","affiliation":"Insight Centre for Data Analytics , University College Dublin"},{"name":"Neil Hurley","slug":"neil-hurley","given":"Neil","family":"Hurley","affiliation":"Insight Centre for Data Analytics , University College Dublin"}],"abstract":"Recent years have seen a rise in smartphone applications promoting health and well being. We argue that there is a large and unexplored ground within the field of recommender systems (RS) for applications that promote good personal health. During the COVID-19 pandemic, with gyms being closed, the demand for at-home fitness apps increased as users wished to maintain their physical and mental health. However, maintaining long-term user engagement with fitness applications has proved a difficult task. Personalisation of the app recommendations that change over time can be a key factor for maintaining high user engagement. In this work we propose a reinforcement learning (RL) based framework for recommending sequences of body-weight exercises to home users over a mobile application interface. The framework employs a user simulator, tuned to feedback a weighted sum of realistic workout rewards, and trains a neural network model to maximise the expected reward over generated exercise sequences. We evaluate our framework within the context of a large 15 week live user trial, showing that an RL based approach leads to a significant increase in user engagement compared to a baseline recommendation algorithm.","doi":"10.24963/ijcai.2023/692","url":"https://ijcai.org/proceedings/2023/692","pdf":"https://ijcai.org/proceedings/2023/0692.pdf","markdown":"https://ijcai.org/proceedings/2023/692.md","bibtex":"https://ijcai.org/proceedings/2023/bibtex/692","volume":{"slug":"2023","title":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2023","url":"https://ijcai.org/proceedings/2023/","year":2023,"location":"Macao, SAR","dates":"19-25 August 2023","editors":"Edith Elkind","isbn":"978-1-956792-03-4","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2023"},"section":"AI for Good","track":"AI for Good","number":692,"pages":{"first":6237,"last":6245},"keywords":["AI for Good: Humans and AI","AI for Good: Agent-based and Multi-agent Systems","AI for Good: Machine Learning","AI for Good: Multidisciplinary Topics and Applications"],"videos":[],"references":[{"position":1,"raw":"[Abdulaziz et al., 2021] Manal Abdulaziz, Bodor Al- motairy, Mona Al-ghamdi, and Norah Al-qahtani. 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