817 research outputs found

    A survey on tasks performed in eldercare

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    In the Netherlands, a vast increase of the expenses on eldercare is expected for the future. Currently, an IT system is under development that aims to assist care providers with their tasks in providing care services. Before such a system can be used in practice, insight is needed on the current work situation in eldercare. This paper presents interview surveys on tasks currently performed by professionals in two nursing houses. Both the professional population and details on how it spends its time are described. Little room is observed for automating tasks in nursing and/or caring houses

    Addressing the Health Needs of an Aging America: New Opportunities for Evidence-Based Policy Solutions

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    This report systematically maps research findings to policy proposals intended to improve the health of the elderly. The study identified promising evidence-based policies, like those supporting prevention and care coordination, as well as areas where the research evidence is strong but policy activity is low, such as patient self-management and palliative care. Future work of the Stern Center will focus on these topics as well as long-term care financing, the health care workforce, and the role of family caregivers

    Artificial Intelligence: Robots, Avatars, and the Demise of the Human Mediator

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    Published in cooperation with the American Bar Association Section of Dispute Resolutio

    Artificial Intelligence: Robots, Avatars, and the Demise of the Human Mediator

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    Published in cooperation with the American Bar Association Section of Dispute Resolutio

    Artificial Intelligence: Robots, Avatars and the Demise of the Human Mediator

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    As technology has advanced, many have wondered whether (or simply when) artificial intelligent devices will replace the humans who perform complex, interactive, interpersonal tasks such as dispute resolution. Has science now progressed to the point that artificial intelligence devices can replace human mediators, arbitrators, dispute resolvers and problem solvers? Can humanoid robots, attractive avatars and other relational agents create the requisite level of trust and elicit the truthful, perhaps intimate or painful, disclosures often necessary to resolve a dispute or solve a problem? This article will explore these questions. Regardless of whether the reader is convinced that the demise of the human mediator or arbitrator is imminent, one cannot deny that artificial intelligence now has the capability to assume many of the responsibilities currently being performed by alternative dispute resolution (ADR) practitioners. It is fascinating (and perhaps unsettling) to realize the complexity and seriousness of tasks currently delegated to avatars and robots. This article will review some of those delegations and suggest how the artificial intelligence developed to complete those assignments may be relevant to dispute resolution and problem solving. “Relational Agents,” which can have a physical presence such as a robot, be embodied in an avatar, or have no detectable form whatsoever and exist only as software, are able to create long term socio-economic relationships with users built on trust, rapport and therapeutic goals. Relational agents are interacting with humans in circumstances that have significant consequences in the physical world. These interactions provide insights as to how robots and avatars can participate productively in dispute resolution processes. Can human mediators and arbitrators be replaced by robots and avatars that not only physically resemble humans, but also act, think, and reason like humans? And to raise a particularly interesting question, can robots, avatars and other relational agents look, move, act, think, and reason even “better” than humans

    Managing Competing Concerns in Digital Innovation:Examining Welfare Technology in Denmark

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    Reinforcement Learning Approaches in Social Robotics

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    This article surveys reinforcement learning approaches in social robotics. Reinforcement learning is a framework for decision-making problems in which an agent interacts through trial-and-error with its environment to discover an optimal behavior. Since interaction is a key component in both reinforcement learning and social robotics, it can be a well-suited approach for real-world interactions with physically embodied social robots. The scope of the paper is focused particularly on studies that include social physical robots and real-world human-robot interactions with users. We present a thorough analysis of reinforcement learning approaches in social robotics. In addition to a survey, we categorize existent reinforcement learning approaches based on the used method and the design of the reward mechanisms. Moreover, since communication capability is a prominent feature of social robots, we discuss and group the papers based on the communication medium used for reward formulation. Considering the importance of designing the reward function, we also provide a categorization of the papers based on the nature of the reward. This categorization includes three major themes: interactive reinforcement learning, intrinsically motivated methods, and task performance-driven methods. The benefits and challenges of reinforcement learning in social robotics, evaluation methods of the papers regarding whether or not they use subjective and algorithmic measures, a discussion in the view of real-world reinforcement learning challenges and proposed solutions, the points that remain to be explored, including the approaches that have thus far received less attention is also given in the paper. Thus, this paper aims to become a starting point for researchers interested in using and applying reinforcement learning methods in this particular research field

    A Review on Usability and User Experience of Assistive Social Robots for Older Persons

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    In the advancement of human-robot interaction technology, assistive social robots have been recognized as one of potential technologies that can provide physical and cognitive supports in older persons care. However, a major challenge faced by the designers is to develop an assistive social robot with prodigious usability and user experience for older persons who were known to have physical and cognitive limitations. A considerable number of published literatures was reporting on the technological design process of assistive social robots. However, only a small amount of attention has been paid to review the usability and user experience of the robots. The objective of this paper is to provide an overview of established researches in the literatures concerning usability and user experience issues faced by the older persons when interacting with assistive social robots. The authors searched relevant articles from the academic databases such as Google Scholar, Scopus and Web of Science as well as Google search for the publication period 2000 to 2021. Several search keywords were typed such as ‘older persons’ ‘elderly’, ‘senior citizens’, ‘assistive social robots’, ‘companion robots’, ‘personal robots’, ‘usability’ and ‘user experience’. This online search found a total of 215 articles which are related to assistive social robots in elderly care. Out of which, 54 articles identified as significant references, and they were examined thoroughly to prepare the main content of this paper. This paper reveals usability issues of 28 assistive social robots, and feedbacks of user experience based on 41 units of assistive social robots. Based on the research articles scrutinized, the authors concluded that the key elements in the design and development of assistive social robots to improve acceptance of older persons were determined by three factors: functionality, usability and users’ experience. Functionality refers to ability of robots to serve the older persons. Usability is ease of use of the robots. It is an indicator on how successful of interaction between the robots and the users. To improve usability, robot designers should consider the limitations of older persons such as vision, hearing, and cognition capabilities when interacting with the robots. User experience reflects to perceptions, preferences and behaviors of users that occur before, during and after use the robots. Combination of superior functionality and usability lead to a good user experience in using the robots which in the end achieves satisfaction of older persons

    A Review on Usability and User Experience of Assistive Social Robots for Older Persons

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    In the advancement of human-robot interaction technology, assistive social robots have been recognized as one of potential technologies that can provide physical and cognitive supports in older persons care. However, a major challenge faced by the designers is to develop an assistive social robot with prodigious usability and user experience for older persons who were known to have physical and cognitive limitations. A considerable number of published literatures was reporting on the technological design process of assistive social robots. However, only a small amount of attention has been paid to review the usability and user experience of the robots. The objective of this paper is to provide an overview of established researches in the literatures concerning usability and user experience issues faced by the older persons when interacting with assistive social robots. The authors searched relevant articles from the academic databases such as Google Scholar, Scopus and Web of Science as well as Google search for the publication period 2000 to 2021. Several search keywords were typed such as ‘older persons’ ‘elderly’, ‘senior citizens’, ‘assistive social robots’, ‘companion robots’, ‘personal robots’, ‘usability’ and ‘user experience’. This online search found a total of 215 articles which are related to assistive social robots in elderly care. Out of which, 54 articles identified as significant references, and they were examined thoroughly to prepare the main content of this paper. This paper reveals usability issues of 28 assistive social robots, and feedbacks of user experience based on 41 units of assistive social robots. Based on the research articles scrutinized, the authors concluded that the key elements in the design and development of assistive social robots to improve acceptance of older persons were determined by three factors: functionality, usability and users’ experience. Functionality refers to ability of robots to serve the older persons. Usability is ease of use of the robots. It is an indicator on how successful of interaction between the robots and the users. To improve usability, robot designers should consider the limitations of older persons such as vision, hearing, and cognition capabilities when interacting with the robots. User experience reflects to perceptions, preferences and behaviors of users that occur before, during and after use the robots. Combination of superior functionality and usability lead to a good user experience in using the robots which in the end achieves satisfaction of older persons

    Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

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    The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications
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