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Technologies 2018, 6(2), 49; https://doi.org/10.3390/technologies6020049

Task Engagement as Personalization Feedback for Socially-Assistive Robots and Cognitive Training

Heracleia Human-Centered Computing Laboratory, Computer Science and Engineering Department, University of Texas at Arlington, Arlington, TX 76010, USA
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Received: 22 February 2018 / Revised: 5 May 2018 / Accepted: 9 May 2018 / Published: 14 May 2018
(This article belongs to the Special Issue Assistive Robotics)
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Abstract

Socially-Assistive Robotics (SAR) has been extensively used for a variety of applications, including educational assistants, exercise coaches and training task instructors. The main goal of such systems is to provide a personalized and tailored session that matches user abilities and needs. While objective measures (e.g., task performance) can be used to adjust task parameters (e.g., task difficulty), towards personalization, it is essential that such systems also monitor task engagement to personalize their training strategies and maximize the effects of the training session. We propose an Interactive Reinforcement Learning (IRL) framework that combines explicit feedback (task performance) with implicit human-generated feedback (task engagement) to achieve efficient personalization. We illustrate the framework with a cognitive training task, describing our data-driven methodology (data collection and analysis, user simulation) towards designing our proposed real-time system. Our data analysis and the reinforcement learning experiments on real user data indicate that the integration of task engagement as human-generated feedback in the RL mechanism can facilitate robot personalization, towards a real-time personalized robot-assisted training system. View Full-Text
Keywords: socially-assistive robotics; personalization; interactive reinforcement learning; brain-computer interfaces socially-assistive robotics; personalization; interactive reinforcement learning; brain-computer interfaces
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Tsiakas, K.; Abujelala, M.; Makedon, F. Task Engagement as Personalization Feedback for Socially-Assistive Robots and Cognitive Training. Technologies 2018, 6, 49.

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