Adaptive Emotional Personality Model based on Fuzzy Logic Interpretation of Five Factor Theory

In recent years, emotional personality has found an important application in the field of human machine interaction. Interesting examples of this domain are computer games, interface agents, human-robot interaction, etc. However, few systems in this area include a model of personality, although it plays an important role in differentiating and determining the way they experience emotions and the way they behave. Personality simulation has always been a complex issue due to the complexity of the human personality itself, and the difficulty to model human psychology on electronic basis. Current efforts for emotion simulation are rather based on predefined set or inputs and its responses or on classical models which are simple approximate and have proven flaws. In this paper an emotional simulation system was presented. It utilizes the latest psychological theories to design a complex dynamic system that reacts to any environment, without being pre-programmed on sets of input. The design was relying on fuzzy logic to simulate human emotional reaction, thus increasing the accuracy by further emulating human brain and removing the pre-defined set of input and its matched output

Towards interoperability of i* models using iStarML

Goal-oriented and agent-oriented modelling provides an effective approach to the understanding of distributed information systems that need to operate in open, heterogeneous and evolving environments. Frameworks, firstly introduced more than ten years ago, have been extended along language variants, analysis methods and CASE tools, posing language semantics and tool interoperability issues. Among them, the i* framework is one the most widespread. We focus on i*-based modelling languages and tools and on the problem of supporting model exchange between them. In this paper, we introduce the i* interoperability problem and derive an XML interchange format, called iStarML, as a practical solution to this problem. We first discuss the main requirements for its definition, then we characterise the core concepts of i* and we detail the tags and options of the interchange format. We complete the presentation of iStarML showing some possible applications. Finally, a survey on the i* community perception about iStarML is included for assessment purposes.Preprin

Approches environnement-centrées pour la simulation de systèmes multi-agents: Pour un déplacement de la complexité des agents vers l'environnement

This habilitation thesis synthesizes research works which are mainly related to the field of Multi-Agent Based Simulation (MABS). MABS is a general framework for modeling and experimenting with systems in which the dynamics emerges from local interactions among individuals (autonomous agents). Examples of use range from the study of natural systems (e.g. ant colonies, crowds or traffic jams) to the engineering of artificial ones (e.g., collective robotics, distributed artificial intelligence-based softwares). To this end, MABS modeling represents the behavior of individuals, their environment and interactions, so that global dynamics can be computed and studied from the bottom up. In this context, we have been investigating research on the theory and practice of MABS from two different perspectives : (1) the design of generic abstractions dedicated to the modeling of multi-agent dynamics (e.g., the IRM4S model) and (2) the engineering of MABS (MaDKit and TurtleKit platforms). Besides, we have been experimenting with MABS in different application domains such as image processing, video games, and collective robotics. Contrary to approaches that put the emphasis on the agent behaviors, all these works have been done by considering the environment of the agents as a first order abstraction. In this thesis, we first reflect upon the research we have conducted according to this perspective. Next, we show how we actually use this perspective to propose an original approach for using General-Purpose processing on Graphics Processing Units (GPGPU) within MABS, and then present the research perspectives related to our positioning.Les travaux de recherche synthétisés dans ce mémoire s’inscrivent principalement dans le domaine de la modélisation et de la simulation de systèmes multi-agents (SMA). La simulation multi-agents met en œuvre des modèles où les individus, leur environnement et leurs interactions sont directement représentés. Dans ces modèles, chaque individu –agent autonome– possède son propre comportement et produit ses actions en fonction d’une perception locale de son environnement. Ainsi, la simulation multi-agents est utilisée pour étudier des systèmes naturels comme les colonies de fourmis, les dynamiques de foules ou le trafic urbain, mais aussi pour concevoir des systèmes artificiels, par exemple dans le cadre de la robotique collective ou le développement de logiciels basés sur de l’intelligence artificielle distribuée. Dans ce cadre, nos recherches ont porté sur des problématiques liées à la modélisation de simulations multi-agents, avec la proposition de modèles formels et conceptuels (e.g. le modèle IRM4S) et d’outils logiciels génériques (plates-formes MaDKit et TurtleKit), et sur leur utilisation dans divers domaines tels que le jeu vidéo, le traitement numérique de l’image ou la robotique collective. Contrairement aux approches centrées sur la conception des comportements individuels, dans ces travaux l’environnement des agents est considéré comme une abstraction de premier ordre. Dans ce mémoire, nous dressons tout d’abord un bilan de nos recherches en argumentant l’intérêt d’une telle démarche pour les modèles multi-agents. Nous montrons ensuite comment celle-ci nous a récemment permis de proposer une approche originale dans le cadre de l’utilisation du calcul haute performance sur carte graphique (GPGPU) pour la simulation de SMA, avant de présenter les perspectives de recherche associées à notre positionnement

An Adaptive Sampling Framework for Life Cycle Degradation Monitoring

Data redundancy and data loss are relevant issues in condition monitoring. Sampling strategies for segment intervals can address these at the source, but do not receive the attention they deserve. Currently, the sampling methods in relevant research lack sufficient adaptability to the condition. In this paper, an adaptive sampling framework of segment intervals is proposed, based on the summary and improvement of existing problems. The framework is implemented to monitor mechanical degradation, and experiments are implemented on simulation data and real datasets. Subsequently, the distributions of the samples collected by different sampling strategies are visually presented through a color map, and five metrics are designed to assess the sampling results. The intuitive and numerical results show the superiority of the proposed method in comparison to existing methods, and the results are closely related to data status and degradation indicators. The smaller the data fluctuation and the more stable the degradation trend, the better the result. Furthermore, the results of the objective physical indicators are obviously better than those of the feature indicators. By addressing existing problems, the proposed framework opens up a new idea of predictive sampling, which significantly improves the degradation monitoring

EmC-ICDSST 2019: 5th International Conference on Decision Support System Technology - ICDSST 2019 & EURO Mini Conference 2019 on "Decision Support Systems: Main Developments & Future Trends"

info:eu-repo/semantics/publishedVersio

Agents and Robots for Reliable Engineered Autonomy

This book contains the contributions of the Special Issue entitled "Agents and Robots for Reliable Engineered Autonomy". The Special Issue was based on the successful first edition of the "Workshop on Agents and Robots for reliable Engineered Autonomy" (AREA 2020), co-located with the 24th European Conference on Artificial Intelligence (ECAI 2020). The aim was to bring together researchers from autonomous agents, as well as software engineering and robotics communities, as combining knowledge from these three research areas may lead to innovative approaches that solve complex problems related to the verification and validation of autonomous robotic systems

Proceedings of The Multi-Agent Logics, Languages, and Organisations Federated Workshops (MALLOW 2010)

http://ceur-ws.org/Vol-627/allproceedings.pdfInternational audienceMALLOW-2010 is a third edition of a series initiated in 2007 in Durham, and pursued in 2009 in Turin. The objective, as initially stated, is to "provide a venue where: the cost of participation was minimum; participants were able to attend various workshops, so fostering collaboration and cross-fertilization; there was a friendly atmosphere and plenty of time for networking, by maximizing the time participants spent together"

Multi-Agent Systems

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

Modelo de privacidad digital en inteligencia ambiental basado en sistemas multiagente

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

Exploiting general-purpose background knowledge for automated schema matching

The schema matching task is an integral part of the data integration process. It is usually the first step in integrating data. Schema matching is typically very complex and time-consuming. It is, therefore, to the largest part, carried out by humans. One reason for the low amount of automation is the fact that schemas are often defined with deep background knowledge that is not itself present within the schemas. Overcoming the problem of missing background knowledge is a core challenge in automating the data integration process. In this dissertation, the task of matching semantic models, so-called ontologies, with the help of external background knowledge is investigated in-depth in Part I. Throughout this thesis, the focus lies on large, general-purpose resources since domain-specific resources are rarely available for most domains. Besides new knowledge resources, this thesis also explores new strategies to exploit such resources. A technical base for the development and comparison of matching systems is presented in Part II. The framework introduced here allows for simple and modularized matcher development (with background knowledge sources) and for extensive evaluations of matching systems. One of the largest structured sources for general-purpose background knowledge are knowledge graphs which have grown significantly in size in recent years. However, exploiting such graphs is not trivial. In Part III, knowledge graph em- beddings are explored, analyzed, and compared. Multiple improvements to existing approaches are presented. In Part IV, numerous concrete matching systems which exploit general-purpose background knowledge are presented. Furthermore, exploitation strategies and resources are analyzed and compared. This dissertation closes with a perspective on real-world applications