No abstract

The COVID-19 pandemic is changing the world in unprecedented and unpredictable ways. Human mobility, being the greatest facilitator for the spread of the virus, is at the epicenter of this change. In order to study mobility under COVID-19, to evaluate the efficiency of mobility restriction policies, and to facilitate a better response to future crisis, we need to understand all possible mobility data sources at our disposal. Our work studies private mobility sources, gathered from mobile-phones and released by large technological companies. These data are of special interest because, unlike most public sources, it is focused on individuals rather than on transportation means. Furthermore, the sample of society they cover is large and representative. On the other hand, these data are not directly accessible for anonymity reasons. Thus, properly interpreting its patterns demands caution. Aware of that, we explore the behavior and inter-relations of private sources of mobility data in the context of Spain. This country represents a good experimental setting due to both its large and fast pandemic peak and its implementation of a sustained, generalized lockdown. Our work illustrates how a direct and naive comparison between sources can be misleading, as certain days (e.g., Sundays) exhibit a directly adverse behavior. After understanding their particularities, we find them to be partially correlated and, what is more important, complementary under a proper interpretation. Finally, we confirm that mobile-data can be used to evaluate the efficiency of implemented policies, detect changes in mobility trends, and provide insights into what new normality means in Spain.

No abstract

Abstract. The concept of Normative Systems can be used in the scope of MultiAgent Systems to provide reliable contexts of interactions between agents where acceptable behaviour is specified in terms of norms. Literature on the topic is growing rapidly, and there is a considerable amount of theoretical frameworks for normative environments, some in the form of Electronic Institutions. Most of these approaches focus on regulative norms rather than on substantive norms, and lack a proper implementation of the ontological connection between brute events and institutional facts. In this paper we present a formalism for the monitoring of both regulative (deontic) and substantive (constitutive) norms based on Structural Operational Semantics, its reduction to Production Systems semantics and our current implementation compliant to these semantics.

Assistive Technologies (AT) are an application area where several Artificial Intelligence techniques and tools have been successfully applied to support elderly or impeded people on their daily activities. However, approaches to AT tend to center in the user-tool interaction, neglecting the user's connection with its social environment (such as caretakers, relatives and health professionals) and the possibility to monitor undesired behaviour providing both adaptation to a dynamic environment and early response to potentially dangerous situations. In previous work we have presented COAALAS, an intelligent social and norm-aware device for elderly people that is able to autonomously organize, reorganize and interact with the different actors involved in elderly-care, either human actors or other devices. In this paper we put our work into context, by first examining what are the desirable properties of such a system, analysing the state-of-the-art on the relevant topics, and verifying the validity of our proposal in a larger context that we call AVICENA. AVICENA's aim is develop a semi-autonomous (collaborative) tool to promote monitored, intensive, extended and personalized therapeutic regime adherence at home based on adaptation techniques.