[pt] O crescimento e a popularidade da web impulsionaram o desenvolvimento de softwares baseados em rede. O uso de sistemas multiagentes (SMAs) nesse contexto é considerado uma abordagem promissora em vem sendo aplicada em diferentes áreas tais como: segurança, missões ou cenários críticos de negócios, monitoramento avançado de ambientes e pessoas, etc., o que significa que analisar as escolhas que este tipo de software pode fazer torna-se crucial. Contudo, as metodologias propostas até o momento pela Engenharia de Software Orientada a Agentes (AOSE) concentraram seus esforços principalmente no desenvolvimento de abordagens disciplinadas para analisar, projetar e implementar um SMA e pouca atenção tem sido dada a forma como tais sistemas podem ser testados. Além disso, no que se refere a testes envolvendo agentes de software, algumas questões relacionadas à observabilidade e a controlabilidade dificultam a tarefa de verificação do comportamento, tais como: (i) a autonomia do agente em seu processo deliberativo; (ii) o fato das crenças e objetivos do agente estarem embutidos no próprio agente, dificultam a observação e controle do comportamento e; (iii) problemas associados à cobertura dos testes. Neste trabalho é apresentada uma nova abordagem para testes unitários de agentes BDI escritos em BDI4JADE baseadas na combinação e adaptação das ideias suportadas pelo JAT Framework, um framework de testes para agentes escritos em JADE e no modelo de faltas proposto por Zhang. / [en] The growth and popularity of the Web has fueled the development of software-based network. The use of multi-agent systems (MAS) in this context is considered a promising approach has been applied in different areas such as security, or mission critical business scenarios, enhanced monitoring of environments and people, etc., which means analyzing the choices that this type of software can become crucial. However, the methodologies proposed so far by the Software Engineering Oriented Agents (AOSE) focused their efforts mainly on developing disciplined approach to analyze, design and implement an SMA and little attention has been given to how such systems can be tested. Furthermore, with regard to tests involving software agents, some issues related to the controllability and observability difficult the task of checking the behavior, such as: (i) the duration of the agent in its decision-making process; (ii) the fact of the agent s beliefs and goals are embedded in the agent itself, hampering the observation and control of behavior; (iii) problems associated with test coverage. In this research a novel approach for unit testing of agents written in BDI4JADE BDI based on the combination and arrangement of ideas supported by JAT Framework, a framework for testing agents written in JADE and fault model proposed by Zhang is displayed.

This thesis deals with designing a model for simulation and visualisation of air combat tactics. It introduces air combat environment and describes a process for its modeling. Thesis describes basics of air combat, its principles and importance of chosen tactics. Using Jason programming language, artificial agents are created and chosen tactics are implemented. The process of implementing tacitcs is described from analysis to final implementation. Finaly, various types of agents are tested in mock combat against each other.

Made available in DSpace on 2014-12-17T15:47:50Z (GMT). No. of bitstreams: 1 AndersonPC.pdf: 869261 bytes, checksum: 91e1d275a5e4a9bad4ad9b5124d11a65 (MD5) Previous issue date: 2008-09-26 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / Intendding to understand how the human mind operates, some philosophers and psycologists began to study about rationality. Theories were built from those studies and nowadays that interest have been extended to many other areas such as computing engineering and computing science, but with a minimal distinction at its goal: to understand the mind operational proccess and apply it on agents modelling to become possible the implementation (of softwares or hardwares) with the agent-oriented paradigm where agents are able to deliberate their own plans of actions. In computing science, the sub-area of multiagents systems has progressed using several works concerning artificial intelligence, computational logic, distributed systems, games theory and even philosophy and psycology. This present work hopes to show how it can be get a logical formalisation extention of a rational agents architecture model called BDI (based in a philosophic Bratman s Theory) in which agents are capable to deliberate actions from its beliefs, desires and intentions. The formalisation of this model is called BDI logic and it is a modal logic (in general it is a branching time logic) with three access relations: B, D and I. And here, it will show two possible extentions that tranform BDI logic in a modal-fuzzy logic where the formulae and the access relations can be evaluated by values from the interval [0,1] / Com o intuito de entender como a mente humana funciona iniciaram-se estudos sobre cogni??o nos campos da filosofia e psicologia. Teorias surgiram desses estudos e, atualmente, esta curiosidade foi estendida a outras ?reas, tais como, ci?ncia e engenharia de computa??o, no entanto, nestas ?reas, o objetivo ? sutilmente diferente: entender o funcionamento da mente e aplic?-lo em uma modelagem artificial. Em ci?ncia da computa??o, a sub-?rea de sistemas multiagentes tem progredido bastante, utilizando trabalhos em intelig?ncia artificial, l?gica computacional, sistemas distribu?dos, teoria dos jogos e, aproveitando tamb?m teorias provenientes da pr?pria filosofia e psicologia. Desta forma, alguns pesquisadores j? v?em o paradigma de programa??o orientado a agentes como a melhor solu??o para a implementa??o dos softwares mais complexos: cujos sistemas s?o din?micos, n?o-determin?sticos e que podem ter de operar com dados faltosos sobre ambientes tamb?m din?micos e n?o-determin?sticos. Este trabalho busca a apresenta??o de uma extens?o da formaliza??o l?gica de um modelo de arquitetura de agentes cognitivos, chamado BDI (belief-desire-intention), na qual o agente ? capaz de deliberar suas a??es baseando-se em suas cren?as, desejos e inten??es. A formaliza??o de tal modelo ? conhecida pelo nome de l?gica BDI, uma l?gica modal com tr?s rela??es de modalidade. Neste trabalho, ser?o apresentados dois planos para transform?-la numa l?gica modal fuzzy onde as rela??es de acessibilidade e as f?rmulas (modais-fuzzy) poder?o ter valora??es dentro do intervalo [0,1]. Esta l?gica modal fuzzy h? de ser um sistema l?gico formal capaz de representar quantitativamente os diferentes graus de cren?as, desejos e inten??es objetivando a constru??o de racioc?nios fuzzy e a delibera??o de a??es de um agente (ou grupo de agentes), atrav?s dessas atitudes mentais (seguindo assim um modelo intensional)

Projektet hade sin bakgrund i önskan att tillhandahålla en virtuell träningsmiljö för lärare där de kan öva på sin icke-verbala kommunikation med elever. Före det här projektet hade utvecklingen av träningsmiljön lett fram till ett visualiserings-system för ett tredimensionellt virtuellt klassrum med animerade karaktärer samt ett system för upptagning och igenkänning av användarens rörelser. För att en sådan träningsmiljö skall vara användbar krävs dock att de virtuella studenterna uppvisar ett trovärdigt mänskligt beteende. Den här rapporten avhandlar implementationen av mänskligt beteende i agenterna förkroppsligade i visualiseringssystemet. För detta ändamål användes det BDI-baserade multi-agent-systemet Jason tillsammans med inspiration från personlighetsteorin OCEAN, affektionsteorin OCC och beteendearkitekturen PMFserv. Rapporten avhandlar även resultatet av ett experiment som utfördes för att utvärdera systemet. I experimentet blev 16 testpersoner introducerade för två olika lärar-scenarion, varpå de, för var och en av dessa scenarion, fyllde i en enkät om deras upplevelse. / The project had its background in the desire to provide a virtual training environment for teachers in which they can exercise their non-verbal communication (e.g. gestures and orientation) with students. Prior to this project, the development of the training environment had led up to a visualisation system for a 3D virtual classroom with virtual students and a motion recognition system for capturing and recognising the user's movements. For such a training environment to be useful however, the virtual students need to express believable human behaviour. This report covers the implementation of human behaviour in the agents embodied in the visualisation system using the BDI-based Jason multi-agent simulation platform with further inspiration taken from the OCEAN personality theory, the OCC theory of emotions and the PMFserv cognitive architecture. It also covers the results of an experiment that was conducted to evaluate the system. During this experiment, 16 test persons were introduced to two different teaching scenarios and were asked to fill in a questionnaire about their experience after each scenario.

La réalité virtuelle joue un rôle majeur dans le développement de nouvelles technologies de l’éducation, et permet de développer des environnements virtuels pour l’apprentissage, dans lesquels, des agents virtuels intelligents jouent le rôle de tuteur. Ces agents sont censés aider les utilisateurs humains à apprendre et appliquer des procédures ayant des objectifs d’apprentissage prédéfini dans différents domaines. Nous travaillons sur la construction d’un système temps-réel capable d’entamer une interaction naturelle avec un utilisateur dans un Environnement d’Apprentissage Virtuel (EAV). Afin d’implémenter ce modèle, nous proposons d’utiliser MASCARET (Multi-Agent System for Collaborative, Adaptive & Realistic Environments for Training) comme modèle d’Environnement Virtuel Intelligent (EVI) afin de représenter la base de connaissances des agents, et de modéliser la sémantique de l’environnement virtuel et des activités des utilisateurs. Afin de formaliser l’intention des agents, nous implémentons un module cognitif dans MASCARET inspiré par l’architecture BDI (Belief-Desire-Intention) qui nous permet de générer des intentions de haut-niveau pour les agents. Dans notre modèle, ces agents sont représentés par des Agents Conversationnels Animés (ACA), qui sont basés sur la plateforme SAIBA (Situation, Agent, Intention, Behavior, Animation). Les agents conversationnels de l’environnement ont des intentions communicatives qui sont transmises à l’utilisateur via des canaux de communication naturels, notamment les actes communicatifs et les comportements verbaux et non-verbaux. Afin d’évaluer notre modèle, nous l’implémentons dans un scénario pédagogique concret pour l’apprentissage des procédures d’analyse de sang dans un laboratoire biomédical. Nous utilisons cette application afin de réaliser une expérimentation et une étude pour valider les propositions de notre modèle. L’hypothèse de notre étude est de supposer que la présence d’un ACA dans un Environnement Virtuel (EV) améliore la performance du processus d’apprentissage (ou qu’au moins, ça ne le dégrade pas) dans le contexte de l’apprentissage d’une procédure spécifique. La performance de l’utilisateur est représentée par le temps requis pour l’exécution de la procédure, le nombre d’erreurs commises et le nombre de demande d’assistance. Nous analysons les résultats de cette évaluation, ce qui confirme partiellement l’hypothèse de l’expérience et affirme que la présence de l’ACA dans l’EV ne dégrade pas la performance de l’apprenant dans le contexte de l’apprentissage d’une procédure. / Virtual Reality plays a major role in developing new educational methodologies, and allows to develop virtual environments for learning where intelligent virtual agents play the role of tutors. These agents are expected to help human users to learn and apply domain-specific procedures with predefined learning outcomes. We work on building a real-time system able to sustain natural interaction with the user in a Virtual Learning Environment (VLE). To implement this model, we propose to use the Multi-Agent System for Collaborative, Adaptive & Realistic Environments for Training (MASCARET) as an Intelligent Virtual Environment (IVE) model that provides the knowledge base to the agents and model the semantic of the virtual environment and user’s activities. To formalize the intention of the agents, we implement a cognitive module within MASCARET inspired by BDI (Belief-Desire-Intention) architecture that permits us to generate high-level intentions for the agents. Furthermore, we integrate Embodied Conversational Agents (ECA), which are based on the SAIBA (Situation, Agent, Intention, Behavior, Animation) framework. The embodied agents of the environment have communicative intentions that are transmitted to the user through natural communication channels, namely the verbal and non-verbal communicative acts and behaviors of the ECAs. To evaluate our model, we implement it in a concrete pedagogical scenario for learning blood analysis procedures in a biomedical laboratory. We use this application to settle an experiment to validate the propositions of our model. The hypothesis of this experiment is to assume that the presence of anECA in a Virtual Environment (VE) enhances the learning performance (or at least does not degrade it) in the context of a learning procedure. The performance is represented by the time of execution, the number of committed errors and the number of requests for assistance. We analyze the results of this evaluation, which partially confirms the hypothesis of the experiment and assure that having an ECA in the VLE does not degrade the performance of the learner in the context of a learning procedure.

Récemment, plusieurs applications, dans lesquelles différentes entités interagissent dans un environnement dynamique, soulignent l’intérêt de l’utilisation des architectures multi-agents. Ces architectures offrent, dans ce cadre, un certain nombre d’avantages, tels que l’autonomie, la réactivité et la capacité de prise de décision. Elles manquent cependant de capacité sociale et de connaissances sur son environnement, notamment lorsqu’il s’agit d’un environnement dynamique. En effet, quand un agent interagit avec le monde réel, il doit prendre en compte les évènements qui peuvent survenir tout en considérant centaines contraintes telles que le temps et l’espace. En outre, les agents doivent faire face à l’incertitude liée aux applications réelles afin de fournir une représentation fidèle du monde réel. Dans le cadre de cette thèse, nous proposons un modèle formel de recommandation des plans qui améliore le processus de prise de décision des agents dans un environnement spatio-temporel et incertain. Pour formaliser les comportements cognitifs des agents dans notre système nommé CARS, en anglais ``Cognitive Agent-based Recommender System '', nous avons étendu l’architecture BDI qui se base sur le modèle `` Croyance-Désir-Intention'' pour prendre en compte les différents contextes liés à des applications réelles en particulier le contexte social. Par ailleurs, nous avons également utilisé la théorie possibiliste afin de considérer l’incertitude dans l’état motivationnel d’un agent (c’est à dire ses croyances, désirs, objectifs ou intentions). Pour répondre aux besoins des applications réelles, tels que les systèmes de recommandation relatives au trafic et navigation, nous proposons une représentation spatiotemporelle des croyances et des intentions d’un agent. Cette représentation permettra l’anticipation de certaines intentions, de manière à recommander un plan qui sera optimal pour un utilisateur. Compte tenu l’incomplétude/l’imprécision liée aux données spatiotemporelles, nous avons étendu le modèle proposé pour raisonner avec des croyances et intentions floues. Une évaluation du modèle proposé a été menée en utilisant une simulation multi-agent, dans un scenario réel de circulation routière. Cette simulation a offert un environnement virtuel qui a mis en lumière, après avoir testé les différentes fonctionnalités du modèle, les principaux points forts ainsi que leslacunes liées à l’architecture multi-agents proposée. / Recently, many real-world applications where different entities interact in a dynamic environment, consider the use of agents in their architectures due principally to their autonomy, reactivity and decision-making abilities. Though these systems can be made intelligent, using Artificial Intelligence (AI) techniques, agents still lack of social abilities and have limited knowledge of their environment and in particular when it comes to a dynamic environment. In fact, when operating in the real world, agents need to deal with unexpected events considering both changes in time and space. Moreover, agents must face the uncertainty, which pervades real-world scenarios in order to provide an accurate representation of the world. In this thesis, we introduce and evaluate a formal framework for recommending plans to agents in the decision making process, when they deal with uncertain spatio-temporal information. The agent-based architecture we propose to address this issue, called CARS (Cognitive Agent-based Recommender System), has been designed by extending the well-known Belief-Desire-Intention (BDI) architecture to incorporate further capabilities to support reasoning with different types of contextual information, including the social context. Uncertainty on the agent's beliefs, desires and intentions is modeled using possibility theory. To meet the requirements of real-world applications, e.g., traffic and navigation recommendation systems, we define a spatio-temporal representation of the agents' beliefs and intentions. Using such a formal framework, anticipatory reasoning about intentional dynamics can be performed with the aim to recommend an optimal plan to a certain user. Since spatio-temporal data is often considered as incomplete and/or vague, we extended the formal framework with a fuzzy representation of spatio-temporal beliefs and intentions. The framework is evaluated through an Agent Based Simulation (ABS) in a real-world traffic scenario. This ABS allowed us to create a virtual environment to test the impact of the different features of our framework as well as to evaluating the main strengths and weaknesses of the proposed agent architecture.

Prozesse, seien es Geschäfts- oder Produktionsprozesse, sind ständigen Änderungen unterworfen. Für Unternehmen gilt es, sich im Rahmen von Geschäftsprozessen immer wieder neuen Marktgegebenheiten, Gesetzen oder Kunden anzupassen. Auch Produktionsprozesse müssen bspw. für die Verarbeitung neuer Materialien zugeschnitten werden. Die vorliegende Arbeit beschreibt deshalb, einen umfassenden Ansatz für den Umgang mit Änderungen bzw. Rekonfigurationen von Workflows zu entwickeln. Dieser zeichnet sich durch zwei Schwerpunkte aus: (1) Vollständige Rekonfiguration aller Workflowperspektiven und (2) eine reflexive autonome Steuerung der Rekonfigurationen.

L'objectif initial de cette thèse est d'apporter une solution à ce problème en proposant, premièrement, une approche cognitive basée sur le paradigme appelé Belief-Desire-Intention (BDI) pour représenter les processus de prise de décision des acteurs humains, et deuxièmement, une validation de cette approche dans le contexte d'un modèle complet de changement d'usage des sols dans lequel la plupart des facteurs cités ci-dessus sont également simulés. Le résultat de ce travail est une approche générique qui a été validée sur un modèle intégrant le changement d'usage des sols d'une région située dans le Delta du Mékong au Vietnam. Nos contributions principales sont les suivantes : Intégration d’une architecture BDI au sein d'une plateforme de modélisation à base d'agents (GAMA) ;Conception d’un cadre générique baptisé « Multi-Agent Based Land-Use Change » (MAB-LUC) permettant de modéliser et de simuler les changements d’usage des sols en prenant en compte les décisions des agriculteurs ;Proposition d’une solution permettant d’intégrer et d’évaluer les facteurs socio-économiques et environnementaux dans le cadre de la planification agraire et d’intégrer MAB-LUC dans le processus existant proposé par la FAO.Ce travail, au-delà du cas d’étude concernant le Delta du Mékong, a enfin été conçu de façon générique afin que la méthodologie utilisée puisse être généralisée à la modélisation de systèmes socio-écologiques où les facteurs humains doivent être représentés avec précision. / The initial goal of this thesis has been then to address this problem by proposing, on one hand, a cognitive approach based on the Belief-Desire-Intention (BDI) paradigm to represent the decision-making processes of human actors in agent-based models and, on the second hand, a validation of this approach in a complete land-use change model in which most of the factors cited above have also been simulated.The outcome of this work is a generic approach, which has been validated in a complex integrated land-use change model of a small region of the Vietnamese Mekong Delta. Our main contributions have been:The integration of the BDI architecture within an agent-based modeling platform (GAMA); The design of the Multi-Agent Based Land-Use Change (MAB-LUC) framework that can take into account the farmers’ decision-making in the land-use change processes;The proposal of a solution to assess the socio-economic and environmental factors in land-use planning and to integrate the MAB-LUC framework into the land-use planning process of. I conclude by showing that this work, designed in a generic fashion, can be reused and generalized for the modeling of complex socio-ecological systems where individual human factors need to be represented accurately.

[pt] A área da saúde desponta como um terreno fértil para a pesquisa científica em Tecnologia da Informação. As atividades de pesquisa na área permitem abordar diversas questões para promover o desenvolvimento tecnológico. Além disso, em relação aos aplicativos para dispositivos móveis, as principais lojas de aplicativos registraram um crescimento significativo no número de aplicativos de saúde disponíveis. Esses crescimentos encontram uma de suas causas na realidade pandêmica que enfrentamos desde o início de 2020. Para lidar com os diferentes desafios de saúde apresentados atualmente, o uso de sistemas multiagentes tem sido considerado uma boa abordagem para lidar, por exemplo, com distribuição, pró-atividade e autonomia dos sistemas. Embora várias plataformas conhecidas utilizem agentes de software, algumas delas não oferecem suporte adequado para o desenvolvimento de agentes, como a plataforma iOS. Assim, nesta dissertação propusemos um framework BDI para iOS que visa apoiar o desenvolvimento de aplicativos móveis de saúde com agentes de software. Esse framework é chamado de Swift Agent Development framework for health (SADE4Health) e usa recursos nativos do iOS, como o Healthkit, que é um repositório central de dados de saúde e condicionamento físico para acessar e compartilhar dados, mantendo a privacidade e o controle do usuário. Para mostrar como o framework suporta o desenvolvimento de novos aplicativos iOS com agentes de software, são explicados os passos mínimos necessários para criar um agente usando os recursos de saúde oferecidos pelo iOS, assim como um cenário de uso modelado a partir deles. Além disso, é apresentado um cenário de uso relacionado ao monitoramento remoto de sinais vitais de pacientes, ilustrando como desenvolver uma instância do framework proposto. Por fim, uma avaliação empírica com desenvolvedores iOS para medir a usabilidade do framework trouxe importantes achados. / [en] The healthcare area is emerging as a fertile ground for scientific research in Information Technology. Research activities in this field allow us to address several issues to promote technological development. In addition, regarding mobile device apps, the leading app stores registered significant growth in the number of available eHealth apps. One of the causes of this growth derives from the pandemic reality we have faced since the beginning of 2020. In order to confront the different health challenges presented currently, the use of multi-agent systems has been considered a good approach, dealing with, for example, distribution, pro-activity and autonomy of systems. Although several known platforms that use software agents, some of them do not offer appropriate support to develop agents, such as the iOS platform. Thus, in this dissertation we have proposed a BDI framework for iOS that aims to support the development of health mobile apps with software agents. This is known as Swift Agent Development Framework for Health (SADE4Health) and it uses native iOS resources, such as Healthkit, comprising a central repository for health and fitness data to access and share data while maintaining the user s privacy and control. To show how the framework supports the development of new iOS apps with software agents, the minimum necessary steps to create an agent using health features offered by iOS are explained, as well as a modeled use scenario based on it. Furthermore, a use scenario related to remote monitoring of patients vital signs that illustrates how to develop an instance of the proposed framework is presented. Finally, an empirical evaluation with iOS developers to measure the framework usability brought important findings.

[pt] O uso de sistemas baseados em agentes é adequado à construção de software complexo. Para garantir uma ordem social desejável é preciso lidar com a autonomia e a diversidade de interesses dos agentes e as normas são mecanismos eficientes de controle usados para regular o comportamento dos agentes. O teste de software continua sendo amplamente aplicado para garantir a qualidade do software. No contexto de sistemas multiagentes normativos, os testes devem lidar com a necessidade dos agentes atuarem de forma robusta sob condições normativas dinâmicas as quais os desenvolvedores não consideraram. Neste contexto, propomos uma abordagem para testar agentes normativos que seguem o modelo belief-desire-intention. Como contribuições, esta tese apresenta: um framework para desenvolvimento de agentes BDI normativos, o NBDI4JADE; um modelo modelo de faltas para apoiar a identificação dos diferentes tipos de falhas em agentes normativos; um framework para testar agentes BDI normativos, o N-JAT4BDI e, um método para geração de casos de teste a partir de modelos ANA-ML dos agentes. Avaliamos o framework de teste através de um estudo experimental no qual discutimos a eficiência e a eficácia do framework. Avaliamos, também, a eficácia do método de geração de casos de teste,aplicando-o a dois cenários de uso: (i) um sistema para gerenciar a submissão e o processo de revisão de artigos em conferências, e (ii) um sistema de venda de pacotes turísticos de uma agência de viagens. Os resultados obtidos nas avaliações de ambos os frameworks apresentam indícios positivos da eficiência e eficácia na detecção e identificação de falhas em agentes normativos e eficiência na geração dos casos de teste. / [en] The use of agent-based systems is suitable for the construction of complex software. To guarantee a desirable social order one we must deal with the autonomy and diversity of interests of the agents and norms are efficient mechanisms of control used to regulate the behavior of the agents. Software testing still have been widely applied to ensure the software quality. In the context of normative multiagent systems, the test must deal with the need for the agents to act robustly under dynamic normative conditions in which the developers did not consider. In this context, we propose an approach to test normative agents that follow the belief-desire-intention model. Among the contributions, this thesis presents: a framework for development of normative BDI agents, the NBDI4JADE; a fault model to support the identification of different types of failures in normative agents; a framework for testing normative BDI agents, the N-JAT4BDI, and a method for generating test cases from ANA-ML models.We evaluated the test framework through an experimental study in which we discussed the efficiency and effectiveness of the framework. We also evaluate the effectiveness of the test case generation method, applying it to two usage scenarios: (i) a system to the manage submission and the review process of articles in conferences, and (ii) a system of sale of tour packages from a travel agency. The results obtained in the evaluations of both frameworks presented positive indications of efficiency and effectiveness in the detection and identification of failures in normative agents and efficiency in the generation of test cases.