Ambient assisted living solutions (AAL) aim to improve the quality of life, especially of elderly with cognitive and physical disabilities, by providing assistive tasks such as medication management, reminders of daily activities or medical tests. However, the loss of physical functions (such as mobility, eyesight and hearing), as well as the loss of cognitive functions (starting from amnesia to severe disabilities as dementia or Alzheimer), require appropriate solutions in order to offer personalised assistive tasks according to user needs and characteristics. In this paper, we propose a novel methodology that is based on the integration of a service-oriented approach with normative reasoning to automatically generate assistive tasks customised for different target user's profiles, and deployable in any AAL environment. The formalisation of the conceptual steps of the methodology is provided, together with a framework implementing them. The advantages of dynamic customisation obtained by decoupling the functional and not functional aspects of assistive technology are shown through a validation scenario.
The paper proposes a new methodological approach for evaluating the comfort condition using the concept of explainable post occupancy to make the user aware of the environmental state in which (s)he works. Such an approach was implemented on a humanoid robot with social capabilities that aims to enforce human engagement to follow recommendations. The humanoid robot helps the user to position the sensors correctly to acquire environmental measures corresponding to the temperature, humidity, noise level, and illuminance. The distribution of the last parameter due to its high variability is also retrieved by the simulation software Dialux. Using the post occupancy evaluation method, the robot also proposes a questionnaire to the user for collecting his/her preferences and sensations. In the end, the robot explains to the user the difference between the suggested values by the technical standards and the real measures comparing the results with his/her preferences and perceptions. Finally, it provides a new classification into four clusters: true positive, true negative, false positive, and false negative. This study shows that the user is able to improve her/his condition based on the explanation given by the robot.
The growing prevalence of interactions between humans and machines, coupled with the rapid development of intelligent and human-like features in technology, necessitates considering the potential implications that an increasingly inter-personal interaction style might have on human behavior. Particularly, since human–human interactions are fundamentally affected by politeness rules, several researchers are investigating if such social norms have some implications also within human–machine interactions. This paper reviews scientific works dealing with politeness issues within human–machine interactions by considering a variety of artificial intelligence systems, such as smart devices, robots, digital assistants, and self-driving cars. This paper aims to analyze scientific results to answer the questions of why technological devices should behave politely toward humans, but above all, why human beings should be polite toward a technological device. As a result of the analysis, this paper wants to outline future research directions for the design of more effective, socially competent, acceptable, and trustworthy intelligent systems.
The increasing development of autonomous intelligent systems, such as smart vehicles, smart homes, and social robots, poses new challenges to face. Among them, ensuring that such systems behave lawfully is one of the crucial topics to be addressed for improving their employment in real contexts of daily life. In this work, we present an approach for norm compliance in the context of open and goal-directed intelligent systems working in dynamic normative environments where goals, services, and norms may change. Such an approach complements a goal-directed system modifying its goals and the way to achieve them for taking norms into accounts, thus influencing the practical reasoning process that goal-oriented systems implement for figuring out what to do. The conformity to norms is established at the goal level rather than at the action level. The effect of a norm that acts at the goal level spreads out at the lower level of actions, thus also improving system flexibility. Recovery mechanisms are provided to face exceptional situations that could be caused by normative changes. A case study in the field of the business organizations is presented for demonstrating the strengths of the proposed solution.
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