{"title":"Interactive Learning and Adaptation for Robot Assisted Therapy for People with Dementia","authors":"K. Tsiakas, Cheryl Abellanoza, F. Makedon","doi":"10.1145/2910674.2935849","DOIUrl":null,"url":null,"abstract":"In this paper, we present an adaptive cognitive music game designed to monitor and improve the attention levels of people with dementia. The goal of this game is to provide a customized protocol based on user needs and preferences, following the Reinforcement Learning (RL) framework. The game adjusts its parameters (e.g., difficulty level) so as to help the user complete the task successfully, while keeping them engaged. The main contribution of this paper is an interactive learning and adaptation framework that enables and facilitates the adaptation of the robot behavior towards new users, providing a safe, tailored and efficient interaction.","PeriodicalId":359504,"journal":{"name":"Proceedings of the 9th ACM International Conference on PErvasive Technologies Related to Assistive Environments","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 9th ACM International Conference on PErvasive Technologies Related to Assistive Environments","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2910674.2935849","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
In this paper, we present an adaptive cognitive music game designed to monitor and improve the attention levels of people with dementia. The goal of this game is to provide a customized protocol based on user needs and preferences, following the Reinforcement Learning (RL) framework. The game adjusts its parameters (e.g., difficulty level) so as to help the user complete the task successfully, while keeping them engaged. The main contribution of this paper is an interactive learning and adaptation framework that enables and facilitates the adaptation of the robot behavior towards new users, providing a safe, tailored and efficient interaction.