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  • 标题:Social Intelligence for a Robot Engaging People in Cognitive Training Activities
  • 作者:Jeanie Chan ; Goldie Nejat
  • 期刊名称:International Journal of Advanced Robotic Systems
  • 印刷版ISSN:1729-8806
  • 电子版ISSN:1729-8814
  • 出版年度:2012
  • 卷号:9
  • 期号:4
  • 页码:113
  • DOI:10.5772/51171
  • 语种:English
  • 出版社:SAGE Publications
  • 摘要:Current research supports the use of cognitive training interventions to improve the brain functioning of both adults and children. Our work focuses on exploring the potential use of robot assistants to allow for these interventions to become more accessible. Namely, we aim to develop an intelligent, socially assistive robot that can engage individuals in person-centred cognitively stimulating activities. In this paper, we present the design of a novel control architecture for the robot Brian 2.0, which enables the robot to be a social motivator by providing assistance, encouragement and celebration during an activity. A hierarchical reinforcement learning approach is used in the architecture to allow the robot to: 1) learn appropriate assistive behaviours based on the structure of the activity, and 2) personalize an interaction based on user states. Experiments show that the control architecture is effective in determining the robot's optimal assistive behaviours during a memory game interaction.
  • 关键词:Socially Assistive Robots; Social Human-Robot Interaction; Control Architecture; Cognitive Interventions
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