13 research outputs found

    Implementing a hardware-embedded reactive agents platform based on a service-oriented architecture over heterogeneous wireless sensor networks

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    Wireless Sensor Networks (WSNs) represent a key technology for collecting important information from different sources in context-aware environments. Unfortunately, integrating devices from different architectures or wireless technologies into a single sensor network is not an easy task for designers and developers. In this sense, distributed architectures, such as service-oriented architectures and multi-agent systems, can facilitate the integration of heterogeneous sensor networks. In addition, the sensors’ capabilities can be expanded by means of intelligent agents that change their behavior dynamically. This paper presents the Hardware-Embedded Reactive Agents (HERA) platform. HERA is based on Services laYers over Light PHysical devices (SYLPH), a distributed platform which integrates a service-oriented approach into heterogeneous WSNs. As SYLPH, HERA can be executed over multiple devices independently of their wireless technology, their architecture or the programming language they use. However, HERA goes one step ahead of SYLPH and adds reactive agents to the platform and also a reasoning mechanism that provides HERA Agents with Case-Based Planning features that allow solving problems considering past experiences. Unlike other approaches, HERA allows developing applications where reactive agents are directly embedded into heterogeneous wireless sensor nodes with reduced computational resources

    Argumentation dialogues in web-based GDSS: an approach using machine learning techniques

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    Tese de doutoramento em InformaticsA tomada de decisão está presente no dia a dia de qualquer pessoa, mesmo que muitas vezes ela não tenha consciência disso. As decisões podem estar relacionadas com problemas quotidianos, ou podem estar relacionadas com questões mais complexas, como é o caso das questões organizacionais. Normalmente, no contexto organizacional, as decisões são tomadas em grupo. Os Sistemas de Apoio à Decisão em Grupo têm sido estudados ao longo das últimas décadas com o objetivo de melhorar o apoio prestado aos decisores nas mais diversas situações e/ou problemas a resolver. Existem duas abordagens principais à implementação de Sistemas de Apoio à Decisão em Grupo: a abordagem clássica, baseada na agregação matemática das preferências dos diferentes elementos do grupo e as abordagens baseadas na negociação automática (e.g. Teoria dos Jogos, Argumentação, entre outras). Os atuais Sistemas de Apoio à Decisão em Grupo baseados em argumentação podem gerar uma enorme quantidade de dados. O objetivo deste trabalho de investigação é estudar e desenvolver modelos utilizando técnicas de aprendizagem automática para extrair conhecimento dos diálogos argumentativos realizados pelos decisores, mais concretamente, pretende-se criar modelos para analisar, classificar e processar esses dados, potencializando a geração de novo conhecimento que será utilizado tanto por agentes inteligentes, como por decisiores reais. Promovendo desta forma a obtenção de consenso entre os membros do grupo. Com base no estudo da literatura e nos desafios em aberto neste domínio, formulou-se a seguinte hipótese de investigação - É possível usar técnicas de aprendizagem automática para apoiar diálogos argumentativos em Sistemas de Apoio à Decisão em Grupo baseados na web. No âmbito dos trabalhos desenvolvidos, foram aplicados algoritmos de classificação supervisionados a um conjunto de dados contendo argumentos extraídos de debates online, criando um classificador de frases argumentativas que pode classificar automaticamente (A favor/Contra) frases argumentativas trocadas no contexto da tomada de decisão. Foi desenvolvido um modelo de clustering dinâmico para organizar as conversas com base nos argumentos utilizados. Além disso, foi proposto um Sistema de Apoio à Decisão em Grupo baseado na web que possibilita apoiar grupos de decisores independentemente de sua localização geográfica. O sistema permite a criação de problemas multicritério e a configuração das preferências, intenções e interesses de cada decisor. Este sistema de apoio à decisão baseado na web inclui os dashboards de relatórios inteligentes que são gerados através dos resultados dos trabalhos alcançados pelos modelos anteriores já referidos. A concretização de cada um dos objetivos permitiu validar as questões de investigação identificadas e assim responder positivamente à hipótese definida.Decision-making is present in anyone’s daily life, even if they are often unaware of it. Decisions can be related to everyday problems, or they can be related to more complex issues, such as organizational issues. Normally, in the organizational context, decisions are made in groups. Group Decision Support Systems have been studied over the past decades with the aim of improving the support provided to decision-makers in the most diverse situations and/or problems to be solved. There are two main approaches to implementing Group Decision Support Systems: the classical approach, based on the mathematical aggregation of the preferences of the different elements of the group, and the approaches based on automatic negotiation (e.g. Game Theory, Argumentation, among others). Current argumentation-based Group Decision Support Systems can generate an enormous amount of data. The objective of this research work is to study and develop models using automatic learning techniques to extract knowledge from argumentative dialogues carried out by decision-makers, more specifically, it is intended to create models to analyze, classify and process these data, enhancing the generation of new knowledge that will be used both by intelligent agents and by real decision-makers. Promoting in this way the achievement of consensus among the members of the group. Based on the literature study and the open challenges in this domain, the following research hypothesis was formulated - It is possible to use machine learning techniques to support argumentative dialogues in web-based Group Decision Support Systems. As part of the work developed, supervised classification algorithms were applied to a data set containing arguments extracted from online debates, creating an argumentative sentence classifier that can automatically classify (For/Against) argumentative sentences exchanged in the context of decision-making. A dynamic clustering model was developed to organize conversations based on the arguments used. In addition, a web-based Group Decision Support System was proposed that makes it possible to support groups of decision-makers regardless of their geographic location. The system allows the creation of multicriteria problems and the configuration of preferences, intentions, and interests of each decision-maker. This web-based decision support system includes dashboards of intelligent reports that are generated through the results of the work achieved by the previous models already mentioned. The achievement of each objective allowed validation of the identified research questions and thus responded positively to the defined hypothesis.I also thank to Fundação para a Ciência e a Tecnologia, for the Ph.D. grant funding with the reference: SFRH/BD/137150/2018

    Intelligent business processes composition based on mas, semantic and cloud integration (IPCASCI)

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    [EN]Component reuse is one of the techniques that most clearly contributes to the evolution of the software industry by providing efficient mechanisms to create quality software. Reuse increases both software reliability, due to the fact that it uses previously tested software components, and development productivity, and leads to a clear reduction in cost. Web services have become are an standard for application development on cloud computing environments and are essential in business process development. These services facilitate a software construction that is relatively fast and efficient, two aspects which can be improved by defining suitable models of reuse. This research work is intended to define a model which contains the construction requirements of new services from service composition. To this end, the composition is based on tested Web services and artificial intelligent tools at our disposal. It is believed that a multi-agent architecture based on virtual organizations is a suitable tool to facilitate the construction of cloud computing environments for business processes from other existing environments, and with help from ontological models as well as tools providing the standard BPEL (Business Process Execution Language). In the context of this proposal, we must generate a new business process from the available services in the platform, starting with the requirement specifications that the process should meet. These specifications will be composed of a semi-free description of requirements to describe the new service. The virtual organizations based on a multi-agent system will manage the tasks requiring intelligent behaviour. This system will analyse the input (textual description of the proposal) in order to deconstruct it into computable functionalities, which will be subsequently treated. Web services (or business processes) stored to be reused have been created from the perspective of SOA architectures and associated with an ontological component, which allows the multi-agent system (based on virtual organizations) to identify the services to complete the reuse process. The proposed model develops a service composition by applying a standard BPEL once the services that will compose the solution business process have been identified. This standard allows us to compose Web services in an easy way and provides the advantage of a direct mapping from Business Process Management Notation diagrams

    μGIM - Microgrid intelligent management system based on a multi-agent approach and the active participation of end-users

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    [ES] Los sistemas de potencia y energía están cambiando su paradigma tradicional, de sistemas centralizados a sistemas descentralizados. La aparición de redes inteligentes permite la integración de recursos energéticos descentralizados y promueve la gestión inclusiva que involucra a los usuarios finales, impulsada por la gestión del lado de la demanda, la energía transactiva y la respuesta a la demanda. Garantizar la escalabilidad y la estabilidad del servicio proporcionado por la red, en este nuevo paradigma de redes inteligentes, es más difícil porque no hay una única sala de operaciones centralizada donde se tomen todas las decisiones. Para implementar con éxito redes inteligentes, es necesario combinar esfuerzos entre la ingeniería eléctrica y la ingeniería informática. La ingeniería eléctrica debe garantizar el correcto funcionamiento físico de las redes inteligentes y de sus componentes, estableciendo las bases para un adecuado monitoreo, control, gestión, y métodos de operación. La ingeniería informática desempeña un papel importante al proporcionar los modelos y herramientas computacionales adecuados para administrar y operar la red inteligente y sus partes constituyentes, representando adecuadamente a todos los diferentes actores involucrados. Estos modelos deben considerar los objetivos individuales y comunes de los actores que proporcionan las bases para garantizar interacciones competitivas y cooperativas capaces de satisfacer a los actores individuales, así como cumplir con los requisitos comunes con respecto a la sostenibilidad técnica, ambiental y económica del Sistema. La naturaleza distribuida de las redes inteligentes permite, incentiva y beneficia enormemente la participación activa de los usuarios finales, desde actores grandes hasta actores más pequeños, como los consumidores residenciales. Uno de los principales problemas en la planificación y operación de redes eléctricas es la variación de la demanda de energía, que a menudo se duplica más que durante las horas pico en comparación con la demanda fuera de pico. Tradicionalmente, esta variación dio como resultado la construcción de plantas de generación de energía y grandes inversiones en líneas de red y subestaciones. El uso masivo de fuentes de energía renovables implica mayor volatilidad en lo relativo a la generación, lo que hace que sea más difícil equilibrar el consumo y la generación. La participación de los actores de la red inteligente, habilitada por la energía transactiva y la respuesta a la demanda, puede proporcionar flexibilidad en desde el punto de vista de la demanda, facilitando la operación del sistema y haciendo frente a la creciente participación de las energías renovables. En el ámbito de las redes inteligentes, es posible construir y operar redes más pequeñas, llamadas microrredes. Esas son redes geográficamente limitadas con gestión y operación local. Pueden verse como áreas geográficas restringidas para las cuales la red eléctrica generalmente opera físicamente conectada a la red principal, pero también puede operar en modo isla, lo que proporciona independencia de la red principal. Esta investigación de doctorado, realizada bajo el Programa de Doctorado en Ingeniería Informática de la Universidad de Salamanca, aborda el estudio y el análisis de la gestión de microrredes, considerando la participación activa de los usuarios finales y la gestión energética de lascarga eléctrica y los recursos energéticos de los usuarios finales. En este trabajo de investigación se ha analizado el uso de conceptos de ingeniería informática, particularmente del campo de la inteligencia artificial, para apoyar la gestión de las microrredes, proponiendo un sistema de gestión inteligente de microrredes (μGIM) basado en un enfoque de múltiples agentes y en la participación activa de usuarios. Esta solución se compone de tres sistemas que combinan hardware y software: el emulador de virtual a realidad (V2R), el enchufe inteligente de conciencia ambiental de Internet de las cosas (EnAPlug), y la computadora de placa única para energía basada en el agente (S4E) para permitir la gestión del lado de la demanda y la energía transactiva. Estos sistemas fueron concebidos, desarrollados y probados para permitir la validación de metodologías de gestión de microrredes, es decir, para la participación de los usuarios finales y para la optimización inteligente de los recursos. Este documento presenta todos los principales modelos y resultados obtenidos durante esta investigación de doctorado, con respecto a análisis de vanguardia, concepción de sistemas, desarrollo de sistemas, resultados de experimentación y descubrimientos principales. Los sistemas se han evaluado en escenarios reales, desde laboratorios hasta sitios piloto. En total, se han publicado veinte artículos científicos, de los cuales nueve se han hecho en revistas especializadas. Esta investigación de doctorado realizó contribuciones a dos proyectos H2020 (DOMINOES y DREAM-GO), dos proyectos ITEA (M2MGrids y SPEAR), tres proyectos portugueses (SIMOCE, NetEffiCity y AVIGAE) y un proyecto con financiación en cascada H2020 (Eco-Rural -IoT)

    Multi-Agent Systems

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    This Special Issue ""Multi-Agent Systems"" gathers original research articles reporting results on the steadily growing area of agent-oriented computing and multi-agent systems technologies. After more than 20 years of academic research on multi-agent systems (MASs), in fact, agent-oriented models and technologies have been promoted as the most suitable candidates for the design and development of distributed and intelligent applications in complex and dynamic environments. With respect to both their quality and range, the papers in this Special Issue already represent a meaningful sample of the most recent advancements in the field of agent-oriented models and technologies. In particular, the 17 contributions cover agent-based modeling and simulation, situated multi-agent systems, socio-technical multi-agent systems, and semantic technologies applied to multi-agent systems. In fact, it is surprising to witness how such a limited portion of MAS research already highlights the most relevant usage of agent-based models and technologies, as well as their most appreciated characteristics. We are thus confident that the readers of Applied Sciences will be able to appreciate the growing role that MASs will play in the design and development of the next generation of complex intelligent systems. This Special Issue has been converted into a yearly series, for which a new call for papers is already available at the Applied Sciences journal’s website: https://www.mdpi.com/journal/applsci/special_issues/Multi-Agent_Systems_2019

    Técnicas de computación social e información contextual para el desarrollo de actividades de aprendizaje colaborativo

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    [EN]Educational innovation is a field in which its processes has been greatly enriched by the use of Information and Communication Technologies (ICT). Thanks to technological advances, the use of learning models where information comes from many different sources is now usual. Likewise, student-student, student-device and device-device collaborations provides added value to the learning processes thanks to the fact that, through it, aspects such as communication, achievement of common goals or sharing resources. Within the educational innovation, we find as a great challenge the development of tools that facilitate the creation of innovative collaborative learning processes that improve the achievement of the objectives sought, with respect to individualized processes, and the fidelity of the students to the process through the use of contextual information. Moreover, the development of these solutions, that facilitate the work of teachers, developers and technicians encouraging the production of educational processes more attractive to students, presents itself as an ambitious challenge in which the perspectives of Ambient Intelligence and Social Computing play a key role. The doctoral dissertation presented here describes and evaluates CAFCLA, a framework specially conceived for the design, development and implementation of collaborative learning activities that make use of contextual information and that is based on the paradigms of Ambient Intelligence and Social Computing. CAFCLA is a flexible framework that covers the entire process of developing collaborative learning activities and hides all the difficulties involved in the use and integration of multiple technologies to its users. In order to evaluate the validity of the proposal, CAFCLA has supported the implementation of three concrete and different use cases. These experimental use cases have shown that, among other benefits, the use of Social Computing customizes the learning process, encourages collaboration, improves relationships, increases commitment, promotes behaviour change in users and enables learning to be maintained over time. In addition, in order to demonstrate the flexibility of the framework, these use cases have been developed in different scenarios (such as a museum, a public building or at home), different types of learning have been proposed (serious games, recommendations system orWebQuest) and different learning objectives have been chosen (academic, social and energy-efficient).[ES]La innovación educativa es un campo que ha sido enormemente enriquecido por el uso de las Tecnologías de la Información y las Comunicaciones (TIC) en sus procesos. Gracias a los avances tecnológicos, actualmente es habitual el uso de modelos de aprendizaje donde la información proviene de numerosas y diferentes fuentes. De igual forma, la colaboración estudiante-estudiante, estudiante-dispositivo y dispositivo-dispositivo, proporciona un valor añadido a los procesos de aprendizaje gracias a que, a través de ella, se fomentan aspectos como la comunicación, la consecución de una meta común, o la compartición de recursos. Dentro de la innovación educativa encontramos como un gran desafío el desarrollo de herramientas que faciliten la creación de procesos de aprendizaje colaborativo innovadores que mejoren los resultados obtenidos, respecto a los procesos individualizados, y la fidelidad de los estudiantes al proceso mediante el uso de información contextual.Más aún, el desarrollo de soluciones que faciliten el trabajo a profesores, desarrolladores y técnicos, fomentando la producción de procesos educativos más atractivos para los estudiantes, se presenta como un ambicioso reto en el que las perspectivas de la Inteligencia Ambiental y la Computación Social juegan un papel fundamental. La tesis doctoral aquí presentada describe y evalúa CAFCLA, un framework especialmente concebido para el diseño, desarrollo e implementación de actividades de aprendizaje colaborativo que hagan uso de información contextual basándose en los paradigmas de la Inteligencia Ambiental y la Computación Social. CAFCLA es un framework flexible que abarca todo el proceso de desarrollo de actividades de aprendizaje colaborativo y oculta todas las dificultades que implican el uso e integración de múltiples tecnologías a sus usuarios. Para evaluar la validez de la propuesta realizada, CAFCLA ha soportado la implementación de tres casos de uso concretos y diferentes entre sí. Estos casos de uso experimentales han demostrado que, entre otros beneficios, el uso de la Computación Social personaliza el proceso de aprendizaje, fomenta la colaboración, mejora las relaciones, aumenta el compromiso, favorecen el cambio de comportamiento en los usuarios y mantiene su implicación en el proceso a lo largo del tiempo. Además, con el objetivo de demostrar la flexibilidad del framework, estos casos de uso se han desarrollado en diferentes escenarios (como un museo, un edificio público o el hogar), se han propuesto diferente tipos de aprendizaje (juegos serios, sistema de recomendaciones o WebQuest) y se han elegido diferentes objetivos de aprendizaje (académicos, sociales y de eficiencia energética)

    Sistemas organizativos para la asignación dinámica de recursos computacionales en entornos distribuidos

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    [ES]Cloud Computing, el conocido paradigma computacional, está emergiendo en los últimos años con gran fuerza. Este paradigma incluye un novedoso modelo de comercialización basado en el pago por uso que ha cambiado radicalmente el modelo de negocio en Internet, lo que ha permitido que las empresas y usuarios individuales puedan alquilar los recursos computacionales que necesitan en cada momento. Este nuevo modelo computacional también ha derivado en que el modelo de producción de estos recursos computacionales evolucione hasta una aproximación cercana al modelo de producción just-in-time, en el que sólo se consumen los recursos necesarios para la producción de los servicios en función de la demanda existente en cada momento, hablándose dentro de este ámbito de elasticidad en los servicios ofertados. Para que esto sea posible, no cabe duda, que una gran cantidad de tecnologías subyacentes han tenido que madurar para dar como resultado un nicho tecnológico con la capacidad para variar los recursos asociados a cada servicio en función de la demanda. Sin embargo, pese a los indudables avances que se han producido a nivel tecnológico, todavía hoy existe una gran capacidad de mejora de estos sistemas. En este sentido, en el marco de esta tesis doctoral se propone el uso de los sistemas multiagente y, especialmente, aquellos basados en modelos organizativos para el control y monitorización de un sistema Cloud Computing. Gracias a esta aproximación, una de las primeras en este campo de investigación, será posible incluir en las plataformas Cloud de nueva generación características derivadas de la Inteligencia Artificial, como son la autonomía, la proactividad y, también, la capacidad de aprendizaje. Para ello se propone un modelo único en su concepción, que permite dotar a la organización de agentes inteligentes con capacidades auto-adaptativas en tiempo de ejecución para entornos abiertos, altamente dinámicos en los que, además, existe un cierto grado de incertidumbre. Así gracias a este modelo, el sistema es capaz de variar los recursos computacionales asociados a cada servicio producido en función de la demanda existe por parte de los usuarios, mediante la auto-adaptación dinámica del propio sistema en su conjunto

    Advances in Public Transport Platform for the Development of Sustainability Cities

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    Modern societies demand high and varied mobility, which in turn requires a complex transport system adapted to social needs that guarantees the movement of people and goods in an economically efficient and safe way, but all are subject to a new environmental rationality and the new logic of the paradigm of sustainability. From this perspective, an efficient and flexible transport system that provides intelligent and sustainable mobility patterns is essential to our economy and our quality of life. The current transport system poses growing and significant challenges for the environment, human health, and sustainability, while current mobility schemes have focused much more on the private vehicle that has conditioned both the lifestyles of citizens and cities, as well as urban and territorial sustainability. Transport has a very considerable weight in the framework of sustainable development due to environmental pressures, associated social and economic effects, and interrelations with other sectors. The continuous growth that this sector has experienced over the last few years and its foreseeable increase, even considering the change in trends due to the current situation of generalized crisis, make the challenge of sustainable transport a strategic priority at local, national, European, and global levels. This Special Issue will pay attention to all those research approaches focused on the relationship between evolution in the area of transport with a high incidence in the environment from the perspective of efficiency

    Modelo de privacidad digital en inteligencia ambiental basado en sistemas multiagente

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    El gran desarrollo de las Tecnologías de la Información y la Comunicación utilizadas en los dominios de aplicación de la Inteligencia Ambiental (AmI), ocurrido en la última década, nos sitúa inmersos en los llamados entornos inteligentes, rodeados de una extensa variedad de dispositivos y tecnologías con capacidad de adquirir, almacenar y transmitir nuestra información personal. La complejidad y volumen de los sistemas involucrados en las aplicaciones desarrolladas en Inteligencia Ambiental hacen que seamos incapaces de conocer y controlar toda la información que estos sistemas son capaces de adquirir y transmitir, tanto si esta información ha sido proporcionada por nosotros directamente, como si ha sido adquirida de forma indirecta por otros sistemas sin nuestro conocimiento; lo que pone en riesgo la protección de nuestro derecho a la privacidad. Considerando que, el principal objetivo de la Inteligencia Ambiental es el de ofrecernos diferentes tipos de servicios personalizados en cualquier lugar y en todo momento, facilitándonos así la realización de nuestras actividades cotidianas, se ha llevado a cabo un estudio sobre las aplicaciones desarrolladas en AmI, que ha revelado la necesidad de incluir las cuestiones de tipo social y ético en el diseño del AmI, destacando entre ellas la privacidad por ser uno de los derechos fundamentales de las personas, como así queda reflejado en la Declaración Universal de los Derechos Humanos (Artículo 12). Por ello, para el verdadero desarrollo y aceptación de la Inteligencia Ambiental deberá considerarse no solo los aspectos tecnológicos, sino que, resulta fundamental tener en cuenta las implicaciones sociales y éticas. Esta es la idea del concepto “Design by Privacy” que se ha utilizado en la investigación realizada. En base a este concepto, se han establecido las políticas de privacidad del usuario según los dominios de aplicación del AmI. Partiendo de la base de que sean las propias técnicas utilizadas en AmI las que ayuden a proteger nuestra información personal, se han utilizado los agentes de los modelos de confianza como herramienta para determinar los derechos de privacidad que deben cumplir los agentes en sus comunicaciones, y que ha servido para decidir con quién compartimos nuestras opiniones privadas, minimizando de esta forma los riesgos de la privacidad de nuestra información al interaccionar con los servicios ofrecidos por las aplicaciones del AmI. Así pues, el motivo de investigación de esta tesis es el de presentar un Modelo de Privacidad Digital basado en Sistemas Multiagente, que nos ayudará a decidir en quién confiar a la hora de compartir nuestras opiniones privadas. Este modelo ha sido implementado para su validación en el entorno de experimentación del ART testbed (Agent Reputation and Trust), en el que el dominio de aplicación del AmI es el relacionado con la tasación de cuadros o pinturas de arte. Una vez implementada la manera de decidir con quién compartimos nuestra información privada, y con el fin de controlar el cumplimiento de los derechos de privacidad que se han establecido en las comunicaciones entre los agentes, se han formalizado las posibles infracciones sobre los derechos de privacidad utilizando la Institución Electrónica “Islander” como herramienta de especificación de las normas y sanciones correspondientes que deben cumplir los agentes en sus comunicaciones.The great development of Information and Communication Technologies used in the domains of application of Ambient Intelligence, which has taken place in the last decade, places us immersed in intelligent environments surrounded by a wide variety of devices and Technologies with the ability to acquire, store and transmit our personal information. The complexity and volume of the systems involved in the applications developed in Environmental Intelligence mean that we are unable to know and control all the information that these systems are able to acquire and transmit, whether this information has been provided by us directly, or whether it has Been acquired indirectly by other systems without our knowledge; Which puts at risk the protection of our right to privacy. Considering that the main objective of Environmental Intelligence is to offer different types of personalized services in any place and at all times, facilitating us to carry out our daily activities, a study has been carried out on the applications developed in AmI, which has revealed the need to take into account social and ethical issues in the design of the AmI, highlighting among them the privacy as one of the fundamental rights of the people, as reflected in the Universal Declaration of Human Rights (Article 12). For that reason, for the true development and acceptance of Ambient Intelligence, not only the technological aspects must be taken into account, but it is fundamental to consider the social and ethical implications. This is the idea of the concept "Design by Privacy" that has been used on the research carried out. Based on this concept, user privacy policies have been established and should be taken into account in the AmI application domains. Based on the idea that the techniques used in AmI are those that help protect our personal information, the agents with a trust model have been used as a tool to determine the privacy rights that agents must comply with in their communications, and that has served to decide with whom we share our private opinions, thus minimizing the risks of privacy of our information when interacting with the services offered by AmI applications. Therefore, the aim of the research of this thesis is to present a Digital Privacy Model based on Multi-Agent Systems, which will help us to decide who to trust when sharing our private opinions. This model has been implemented for validation in the experimental environment of the ART testbed (Agent Reputation and Trust), in which the domain of the AmI application, is the one related with the evaluation of art pictures. Once the way to decide with whom we share our private information has been implemented, and in order to control the compliance with the privacy rights established in the communications between the agents, possible violations of privacy rights have been formalized using the Electronic Institution "Islander" as a tool for specifying the standards and corresponding sanctions that agents must comply with in their communications.Programa Oficial de Doctorado en Ciencia y Tecnología InformáticaPresidente: Jesús García Herrero.- Secretario: Clara Benac Earle.- Vocal: Ana María Bernardos Barboll

    Modelling a conversational agent (Botocrates) for promoting critical thinking and argumentation skills

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    Students in higher education institutions are often advised to think critically, yet without being guided to do so. The study investigated the use of a conversational agent (Botocrates) for supporting critical thinking and academic argumentation skills. The overarching research questions were: can a conversational agent support critical thinking and academic argumentation skills? If so, how? The study was carried out in two stages: modelling and evaluating Botocrates' prototype. The prototype was a Wizard-of-Oz system where a human plays Botocrates' role by following a set of instructions and knowledge-base to guide generation of responses. Both stages were conducted at the School of Education at the University of Leeds. In the first stage, the study analysed 13 logs of online seminars in order to define the tasks and dialogue strategies needed to be performed by Botocrates. The study identified two main tasks of Botocrates: providing answers to students' enquiries and engaging students in the argumentation process. Botocrates’ dialogue strategies and contents were built to achieve these two tasks. The novel theoretical framework of the ‘challenge to explain’ process and the notion of the ‘constructive expansion of exchange structure’ were produced during this stage and incorporated into Botocrates’ prototype. The aim of the ‘challenge to explain’ process is to engage users in repeated and constant cycles of reflective thinking processes. The ‘constructive expansion of exchange structure’ is the practical application of the ‘challenge to explain’ process. In the second stage, the study used the Wizard-of-Oz (WOZ) experiments and interviews to evaluate Botocrates’ prototype. 7 students participated in the evaluation stage and each participant was immediately interviewed after chatting with Botocrates. The analysis of the data gathered from the WOZ and interviews showed encouraging results in terms of students’ engagement in the process of argumentation. As a result of the role of ‘critic’ played by Botocrates during the interactions, users actively and positively adopted the roles of explainer, clarifier, and evaluator. However, the results also showed negative experiences that occurred to users during the interaction. Improving Botocrates’ performance and training users could decrease users’ unsuccessful and negative experiences. The study identified the critical success and failure factors related to achieving the tasks of Botocrates
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