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With the current advance of technology, agent-based applications are becoming a standard in a great variety of domains such as e-commerce, logistics, supply chain management, telecommunications, healthcare, and manufacturing. Another reason for the widespread interest in multi-agent systems is that these systems are seen as a technology and a tool that helps in the analysis and development of new models and theories in large-scale distributed systems or in human-centered systems. This last aspect is currently of great interest due to the need for democratization in the use of technology that allows people without technical preparation to interact with the devices in a simple and coherent way. In this Special Issue, different interesting approaches that advance this research discipline have been selected and presented.

Recent studies show that the elderly population has increased considerably in European society in recent years. This fact has led the European Union and many countries to propose new policies for caring services directed to this group. The current trend is to promote the care of the elderly in their own homes, thus avoiding inverting resources on residences. With this in mind, there are now new solutions in this direction, which try to make use of the continuous advances in computer science. This paper tries to advance in this area by proposing the use of a personal assistant to help older people at home while carrying out their daily activities. The proposed personal assistant is called ME3CA, and can be described as a cognitive assistant that offers users a personalised exercise plan for their rehabilitation. The system consists of a sensorisation platform along with decision-making algorithms paired with emotion detection models. ME3CA detects the users&rsquo ; emotions, which are used in the decision-making process allowing for more precise suggestions and an accurate (and unbiased) knowledge about the users&rsquo ; opinion towards each exercise.

[EN] In the last few years, we witnessed a growing body of literature about automated negotiation. Mainly, negotiating agents are either purely self-driven by maximizing their utility function or by assuming a cooperative stance by all parties involved in the negotiation. We argue that, while optimizing one's utility function is essential, agents in a society should not ignore the opponent's utility in the final agreement to improve the agent's long-term perspectives in the system. This article aims to show whether it is possible to design a social agent (i.e., one that aims to optimize both sides' utility functions) while performing efficiently in an agent society. Accordingly, we propose a social agent supported by a portfolio of strategies, a novel tit-for-tat concession mechanism, and a frequency-based opponent modeling mechanism capable of adapting its behavior according to the opponent's behavior and the state of the negotiation. The results show that the proposed social agent not only maximizes social metrics such as the distance to the Nash bargaining point or the Kalai point but also is shown to be a pure and mixed equilibrium strategy in some realistic agent societies. ; This work was partially supported by the MINECO/FEDER RTI2018-095390-B-C31 project of the Spanish government and partially supported by a grant of The Scientific and Research Council of Turkey (TUBITAK) with grant number 118E197. The contents of this article reflect the ideas and positions of the authors and do not necessarily reflect the ideas or positions of TUBITAK. ; Sanchez-Anguix, V.; Tunali, O.; Aydogan, R.; Julian, V. (2021). Can Social Agents Efficiently Perform in Automated Negotiation?. Applied Sciences. 11(13):1-26. https://doi.org/10.3390/app11136022 ; S ; 1 ; 26 ; 11 ; 13

The great demographic change leading to an ageing society demands technological solutions to satisfy the increasing varied elderly needs. This paper presents PHAROS, an interactive robot system that recommends and monitors physical exercises designed for the elderly. The aim of PHAROS is to be a friendly elderly companion that periodically suggests personalised physical activities, promoting healthy living and active ageing. Here, it is presented the PHAROS architecture, components and experimental results. The architecture has three main strands: a Pepper robot , that interacts with the users and records their exercises performance; the Human Exercise Recognition , that uses the Pepper recorded information to classify the exercise performed using Deep Leaning methods; and the Recommender , a smart-decision maker that schedules periodically personalised physical exercises in the users' agenda. The experimental results show a high accuracy in terms of detecting and classifying the physical exercises (97.35%) done by 7 persons. Furthermore, we have implemented a novel procedure of rating exercises on the recommendation algorithm. It closely follows the users' health status (poor performance may reveal health problems) and adapts the suggestions to it. The history may be used to access the physical condition of the user, revealing underlying problems that may be impossible to see otherwise. ; This work was partly supported by the FCT - Fundação para a Ciência e Tecnología through the Post-Doc scholarship SFRH/BPD/102696/2014 and by the Spanish Government TIN2016-76515-R and TIN2015-65515-C4-1-R Grants supported with Feder funds. ...

Recent studies show that the elderly population has increased considerably in European society in recent years. This fact has led the European Union and many countries to propose new policies for caring services directed to this group. The current trend is to promote the care of the elderly in their own homes, thus avoiding inverting resources on residences. With this in mind, there are now new solutions in this direction, which try to make use of the continuous advances in computer science. This paper tries to advance in this area by proposing the use of a personal assistant to help older people at home while carrying out their daily activities. The proposed personal assistant is called ME(3)CA, and can be described as a cognitive assistant that offers users a personalised exercise plan for their rehabilitation. The system consists of a sensorisation platform along with decision-making algorithms paired with emotion detection models. ME(3)CA detects the users' emotions, which are used in the decision-making process allowing for more precise suggestions and an accurate (and unbiased) knowledge about the users' opinion towards each exercise.

In this work, we propose the introduction of persuasion techniques that guide the users into interacting with the Ambient Assisted Living framework iGenda. It is a cognitive assistant that manages active daily living activities, monitors user's health condition, and creates a social network between users via mobile devices. The objective is to be inserted in a healthcare environment and to provide features like adaptive interfaces, user profiling and machine learning processes that enhance the usage experience. The inclusion of a persuasive architecture (based on argumentation schemes) enables the system to provide recommendations to the users that fit their profile and interests, thus increases the chance of a positive interaction. ; A. Costa thanks the Fundacao para a Ciencia e a Tecnologia (FCT) the Post-Doc scholarship with the Ref. SFRH/BPD/102696/2014. This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT - Fundacao para a Ciencia e a Tecnologia within the Project Scope: UID/CEC/00319/2013. It was also supported by the by the projects TIN2015-65515-C4-1-R and TIN2014-55206-R of the Spanish government and by the grant program for the recruitment of doctors for the Spanish system of science and technology (PAID-10-14) of the Universitat Politecnica de Valencia. ...

In this paper, we present in depth the hardware components of a low-cost cognitive assistant. The aim is to detect the performance and the emotional state that elderly people present when performing exercises. Physical and cognitive exercises are a proven way of keeping elderly people active, healthy, and happy. Our goal is to bring to people that are at their homes (or in unsupervised places) an assistant that motivates them to perform exercises and, concurrently, monitor them, observing their physical and emotional responses. We focus on the hardware parts and the deep learning models so that they can be reproduced by others. The platform is being tested at an elderly people care facility, and validation is in process. ; This work was partly supported by the FCT (Fundação para a Ciência e Tecnología) through the Post-Doc scholarship SFRH/BPD/102696/2014 (A. Costa), by the Generalitat Valenciana (PROMETEO/2018/002), and by the Spanish Government ...

The increase in the elderly population in today's society entails the need for new policies to maintain an adequate level of care without excessively increasing social spending. One of the possible options is to promote home care for the elderly. In this sense, this paper introduces a personal assistant designed to help elderly people in their activities of daily living. This system, called EMERALD, is comprised of a sensing platform and different mechanisms for emotion detection and decision-making that combined produces a cognitive assistant that engages users in Active Aging. The contribution of the paper is twofold—on the one hand, the integration of low-cost sensors that among other characteristics allows for detecting the emotional state of the user at an affordable cost; on the other hand, an automatic activity suggestion module that engages the users, mainly oriented to the elderly, in a healthy lifestyle. Moreover, by continuously correcting the system using the on-line monitoring carried out through the sensors integrated in the system, the system is personalized, and, in broad terms, emotionally intelligent. A functional prototype is being currently tested in a daycare centre in the northern area of Portugal where preliminary tests show positive results. ; This research was partially funded by the Fundacao para a Ciencia e Tecnologia (FCT) within the projects UID/CEC/00319/2019 and Post-Doc Grant SFRH/BPD/102696/2014 (Angelo Costa). This work is also partially funded by the MINECO/FEDER TIN2015-65515-C4-1-R and RISEWISE (RISEWomen with disabilities In Social Engagement) EU project under Agreement No. 690874. ...

Over the last decades inside and outside of Europe, treatment-based data have been used in epidemiological research on drugs and drug abuse. They offer information on hidden populations and allow to follow socially stigmatised behaviour. As this type of research can be done on rather low budgets, there are long-term projects run in many countries. Experts from the national systems in several EU member states have been working together to develop a common standard on the basis of the Pompidou Group (PG) Definitive Protocol. The items and basic definitions of the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA)/PG Treatment Demand Indicator Protocol are described, which plays an important role in the process of harmonisation of data collection for the EMCDDA. Implementation strategies are described, and future steps are discussed.

This paper proposes the development of a system to integrally control the activities carried out by a group of elderly people in a nursing home. The system is basically composed of a robot and an app that proposes activities, and also an individual wristband that monitors each elderly person to detect if they get bored or have fun doing the activities. As com-mented, the system also includes an app that, among other things, allows the caregiver to monitor the activities of the group or in an individualized way. ; GVA - Generalitat Valenciana(PROMETEO/2018/002). e FCT-Fundac¸ao para a Ci ˜ encia e Tecnolog ˆ ´ıa through the Post-Doc scholarship SFRH/BPD/102696/2014 (A. Costa), by the Generalitat Valenciana (PROMETEO/2018/002), by Universitat Politecnica de Valencia research grant (PAID-10-19) and by the Spanish Government ...

Ambient Assisted Living provides solutions to the increasing cognitive problems that affect the elderly population. To provide all features possible, Ambient Assisted Living projects require access to personal and private information of their users. Currently, the legal issues arisen in Ambient Assisted Living are a hot topic in the European Union, especially aspects regarding unsupervised data processing and cross-sharing of personal information. In this paper it is presented the iGenda project, which is a Cognitive Assistant inserted in the Ambient Assisted Living area which aims to build safe environments that adapt themselves to one's individual needs. However, one of the issues is the protection of the data flowing within the system and the protection of user's fundamental rights. It is also presented the principles and legal guarantees of data protection and transmission, and legal aspects are explained, embracing appropriate solutions to technological features that may be a threat. ; FEDER - Federación Española de Enfermedades Raras(TIN2015-65515-C4-1-R). COMPETE: POCI-01-0145-FEDER-007043 and FCT-Fundação para a Ciência e Tecnologia within the Project Scope UID/ CEC/00319/2013. A. Costa thanks the Fundação para a Ciência e a Tecnologia (FCT) the Post-Doc scholarship with the Ref. SFRH/BPD/102696/2014. This work is also partially supported by the MINECO/FEDER ...

<b><i>Background:</i></b> Cocaine-related health consequences are difficult to observe. Data on drug users in health-emergency settings may be a useful source of information on consequences that are not visible via other information sources. <b><i>Methods:</i></b> Thirty European countries submit an annual national report on the drug situation to the EMCDDA. All reports for the period 2007–2010 were analyzed, with particular attention given to auditing cocaine-related mentions. Analysis was also performed in order to identify sources and case definitions, assess coverage, audit cases and, where possible, to identify long-term trends. <b><i>Results:</i></b> Considerable heterogeneity existed between countries in their approach to recording drug-related emergencies, with only Spain and the Netherlands having established formal indicators. The highest annual numbers of cocaine-related episodes were reported by the UK (3,502), Spain (2,845) and the Netherlands (1,211). A considerable (2- to 3-fold) increase in the numbers of cocaine-related episodes has been reported since the end of the 1990s in these countries; these increases peaked in Spain and England around 2007/08. <b><i>Conclusions:</i></b> The analysis reported here suggests the need to develop more standardized approaches to monitoring drug-related emergencies. It points to the potential value of developing effective referral links between the emergency and specialized drug services working with cocaine users.

The standardization of cannabis doses is a priority for research, policy-making, clinical and harm-reduction interventions and consumer security. Scientists have called for standard units of dosing for cannabis, similar to those used for alcohol. A Standard Joint Unit (SJU) would facilitate preventive and intervention models in ways similar to the Standard Drink (SD). Learning from the SD experiences allows researchers to tackle emerging barriers to the SJU by applying modern forecasting methods. During a workshop at the Lisbon Addictions Conference 2019, a back-casting foresight method was used to address challenges and achieve consensus in developing an SJU. Thirty-two professionals from 13 countries and 10 disciplines participated. Descriptive analysis of the workshop was carried out by the organizers and shared with the participants in order to suggest amendments. Several characteristics of the SJU were defined: (1) core values: easy-to use, universal, focused on THC, accurate, and accessible; (2) key challenges: sudden changes in patterns of use, heterogeneity of cannabis compounds as well as in administration routes, variations over time in THC concentrations, and of laws that regulate the legal status of recreational and medical cannabis use); and (3) facilitators: previous experience with standardized measurements, funding opportunities, multi-stakeholder support, high prevalence of cannabis users, and widespread changes in legislation. Participants also identified three initial steps for the implementation of a SJU by 2030: (1) Building a task-force to develop a consensus-based SJU; (2) Expanded available national-level data; (3) Linking SJU consumption to the concept of "risky use," based on evidence of harms.