Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal.

Les travaux présentés dans cette thèse s'inscrivent dans une problématique d'aide à la conception de systèmes, à la planification de leur projet de développement et à leur couplage. L'aide à la conception et à la planification repose sur la formalisation de deux grands types de connaissances : les connaissances méthodologiques utilisables quel que soit le projet de conception et, les connaissances métier spécifiques à un type de conception et/ou de planification donné. Le premier chapitre de la thèse propose un état de l'art concernant les travaux sur le couplage des processus de conception de systèmes et de planification des projets associés et expose la problématique de nos travaux. Deux partie traitent ensuite, d'une part, des connaissances méthodologiques et, d'autre part, des connaissances métier. La première partie expose trois types de couplages méthodologiques. Le couplage structurel propose de formaliser les entités de conception et de planification puis permet leur création et leur association. Le couplage informationnel définit les attributs de faisabilité et de vérification pour ces entités et synchronise les états de ces dernières vis-à-vis de ces attributs. Enfin, le couplage décisionnel consiste à proposer, dans un même espace et sous forme de tableau de bord, les informations nécessaires et suffisantes à la prise de décision par les acteurs du projet de conception. La seconde partie propose de formaliser, d'exploiter et de capitaliser la connaissance métier. Après avoir formalisé ces connaissances sous forme d'une ontologie de concepts, deux mécanismes sont exploités : un mécanisme de réutilisation de cas permettant de réutiliser, en les adaptant, les projets de conception passés et un mécanisme de propagation de contraintes permettant de propager des décisions de la conception vers la planification et réciproquement. / The work presented in this thesis deals with aiding system design, development project planning and its coupling. Aiding design and planning is based on the formalization of two kind of knowledge: methodological knowledge that can be used in all kind of design projects and business knowledge that are dedicated to a particular kind of design and/or planning. The first chapter presents a state of the art about coupling system design process and project planning process and gives the problem of our work. Then, two parts deal with design and planning coupling thanks to, on one hand, methodological knowledge, and on the other hand, business knowledge. The first part presents three types of methodological coupling. The structural coupling defines design and planning entities and permits its simultaneous creation of and its association. The informational coupling defines feasibility and verification attributes for these entities and synchronizes its attribute states. Finally, the decisional coupling consists in proposing, in a single dashboard, the necessary and sufficient information to make a decision by the design project actors. The second part proposes to formalize, to exploit and to capitalize business knowledge. This knowledge is formalized with ontology of concepts. Then, two mechanisms are exploited: a case reuse mechanism that permits to reuse and adapt former design projects and a constraint propagation mechanism that allows propagating decisions from design to planning and reciprocally.

[pt] Durante as etapas iniciais de design, o designer forma um entendimento inicial sobre o problema que ele deve resolver e desenvolve suas primeiras ideias, geralmente influenciadas por conhecimentos de design passados. Com o objetivo de auxiliar o design de IHC (interação humano-computador) neste contexto, nós investigamos como podemos usar o raciocínio baseado em casos (CBR) para ajudar designers a acessar e reutilizar conhecimentos de design para resolver novos problemas de IHC. Nós conduzimos entrevistas com designers de IHC profissionais para coletar dados sobre como eles lidam com problemas de design e suas motivações e expectativas sobre o uso de conhecimentos de design auxiliado por uma ferramenta de CBR. Usando estes dados, construímos uma ferramenta, chamada CHIDeK, que contém uma biblioteca contendo casos de design de IHC e fornece acesso aos casos através de navegação facetada, links diretos entre casos e busca. Para investigar como o CHIDeK influencia a atividade de design, conduzimos um estudo que simulava a etapa inicial de design de IHC de um sistema online de reserva de bicicletas. Alguns participantes podiam resolver o problema enquanto tinham acesso ao CHIDeK e outros deviam resolver sem o CHIDeK. Descobrimos que os casos no CHIDeK ajudaram o design motivando o processo de reflexão dos designers, ativando memórias de experiências com sistemas similares aos descritos nos casos e ajudando a gerar novas ideias. Também identificamos algumas limitações na representação dos casos, o que oferece oportunidade para novas pesquisas. Comparando ambos os tipos de atividade de design, percebemos que os designers sem a biblioteca de casos usaram a mesma solução para um dos itens descrito no cenário do estudo, enquanto os designers com os casos variaram entre duas soluções. Concluímos dizendo que uma ferramenta de CBR tem muito potencial para ajudar na atividade de design, porém existem problemas que devem ser endereçados por pesquisas futuras. / [en] During the early stages of design, the designer forms an initial understanding about the problem and some ideas on how to solve it, often influenced by previous design knowledge. In order to support HCI design in this context, we investigated ways to use case-based reasoning (CBR) to help designers access and reuse design knowledge to solve new HCI design problems. We conducted interviews with professional HCI designers to collect data about how they deal with design problems, and their motivations and expectations regarding the use of design knowledge aided by a CBR tool. Using this data, we designed and developed a tool called CHIDeK, which has a library containing HCI design cases and provides access to them through faceted navigation, direct links between cases, and search. To investigate the way CHIDeK influences the design activity, we conducted a study that simulated the early stage of HCI design of an online bike reservation system. Some participants could solve the problem while having access to CHIDeK and others had to solve it without CHIDeK. We discovered that the cases from CHIDeK supported the design by motivating the designers reflective process, triggering their memories of experiences with systems similar to the ones in cases, and helping generate new ideas. We also identified some limitations in the case representation, which offers an opportunity for further research. When comparing both kinds of design activities, we noticed that designers without the case library used the same solution for one of the issues described in the study scenario, while the designers with the cases varied between two solutions. We concluded that a CBR tool has much potential to aid the design activity, but there are still issues that need to be addressed by further research.

Cette thèse propose un modèle permettant la mise en œuvre d'un système de raisonnement à partir de cas capable d'adapter des procédures représentées sous forme de texte en langue naturelle, en réponse à des requêtes d'utilisateurs. Bien que les cas et les solutions soient sous forme textuelle, l'adaptation elle-même est d'abord appliquée à un réseau de contraintes temporelles exprimées à l'aide d'une algèbre qualitative, grâce à l'utilisation d'un opérateur de révision des croyances. Des méthodes de traitement automatique des langues sont utilisées pour acquérir les représentations algébriques des cas ainsi que pour regénérer le texte à partir du résultat de l'adaptation / This thesis proposes a practical model making it possible to implement a case-based reasoning system that adapts processes represented as natural language text in response to user queries. While the cases and the solutions are in textual form, the adaptation itself is performed on networks of temporal constraints expressed with a qualitative algebra, using a belief revision operator. Natural language processing methods are used to acquire case representations and to regenerate text based on the adaptation result

Made available in DSpace on 2016-12-23T14:33:36Z (GMT). No. of bitstreams: 1 dissertacao.pdf: 2123194 bytes, checksum: b9d4a5d39eaf88559d7055b13547ab8e (MD5) Previous issue date: 2006-11-27 / Due to the complexity and the high number of variables involved in the management activities, it is essential to the project manager to have some kind of automated support to perform her tasks. During the accomplishment of a software project, a high amount of knowledge is produced and used. Looking for the reuse of that knowledge in future projects, we need to provide means to retain and store the generated knowledge in a way to minimize the effort to obtain it in the future. In this context, knowledge management can be used to capture the knowledge and experience generated and accumulated during the software process and to promote the appearance of new knowledge. Experience constitutes a key factor in order to management activities can be accomplished with success. Thus, the benefits reached by the change of ideas during the accomplishment of those activities are evident. During this work, in order to support software project management using knowledge management in the software development environment ODE, we have developed and integrated to ODE an infrastructure to support software items characterization and search for similar items and an infrastructure to support group decision. To evaluate the potential of these infrastructures, we specialized them, respectively, to support project characterization and cooperative elaboration of risk plans. / Tendo em vista a complexidade das atividades de gerência e a quantidade de variáveis envolvidas nessas atividades, é essencial que o gerente de projetos conte com algum tipo de apoio automatizado para realizá-las. Durante a realização de um projeto de software, muito conhecimento é produzido e utilizado. Visando à reutilização desse conhecimento em projetos futuros, é fundamental que sejam providos meios de se reter e armazenar o conhecimento gerado, de forma a minimizar o esforço para obtê-lo no futuro. Neste contexto, a gerência de conhecimento pode ser usada para capturar o conhecimento e a experiência gerada e acumulada durante o processo de software e promover o surgimento de novo conhecimento. A experiência constitui um fator de fundamental importância para que as atividades de gerência sejam realizadas com sucesso. Assim, os benefícios alcançados pela troca de idéias durante a realização dessas atividades são evidentes. Durante este trabalho, visando ao apoio de gerência de conhecimento à gerência de projetos de software no ambiente de desenvolvimento de software ODE, foram desenvolvidas e integradas a ODE uma infra-estrutura para caracterização de itens de software e busca de itens similares e uma infra-estrutura de apoio à decisão em grupo. Para avaliar o potencial dessas infra-estruturas, foram conduzidas especializações das mesmas, respectivamente, para caracterização de projetos e para a elaboração cooperativa de planos de riscos.

Made available in DSpace on 2016-12-23T14:33:37Z (GMT). No. of bitstreams: 1 dissertacao.pdf: 8391728 bytes, checksum: 9bece3ebe6f8b8e7853c4336a5dd29f5 (MD5) Previous issue date: 2006-09-10 / Tendo em vista a complexidade das atividades de gerência e a quantidade de variáveis envolvidas nessas atividades, é essencial que o gerente de projetos conte com algum tipo de apoio automatizado para realizá-las. Durante a realização de um projeto de software, muito conhecimento é produzido e utilizado. Visando à reutilização desse conhecimento em projetos futuros, é fundamental que sejam providos meios de se reter e armazenar o conhecimento gerado, de forma a minimizar o esforço para obtê-lo no futuro. Neste contexto, a gerência de conhecimento pode ser usada para capturar o conhecimento e a experiência gerada e acumulada durante o processo de software e promover o surgimento de novo conhecimento. A experiência constitui um fator de fundamental importância para que as atividades de gerência sejam realizadas com sucesso. Assim, os benefícios alcançados pela troca de idéias durante a realização dessas atividades são evidentes. Durante este trabalho, visando ao apoio de gerência de conhecimento à gerência de projetos de software no ambiente de desenvolvimento de software ODE, foram desenvolvidas e integradas a ODE uma infra-estrutura para caracterização de itens de software e busca de itens similares e uma infra-estrutura de apoio à decisão em grupo. Para avaliar o potencial dessas infra-estruturas, foram conduzidas especializações das mesmas, respectivamente, para caracterização de projetos e para a elaboração cooperativa de planos de riscos. / Due to the complexity and the high number of variables involved in the management activities, it is essential to the project manager to have some kind of automated support to perform her tasks. During the accomplishment of a software project, a high amount of knowledge is produced and used. Looking for the reuse of that knowledge in future projects, we need to provide means to retain and store the generated knowledge in a way to minimize the effort to obtain it in the future. In this context, knowledge management can be used to capture the knowledge and experience generated and accumulated during the software process and to promote the appearance of new knowledge. Experience constitutes a key factor in order to management activities can be accomplished with success. Thus, the benefits reached by the change of ideas during the accomplishment of those activities are evident. During this work, in order to support software project management using knowledge management in the software development environment ODE, we have developed and integrated to ODE an infrastructure to support software items characterization and search for similar items and an infrastructure to support group decision. To evaluate the potential of these infrastructures, we specialized them, respectively, to support project characterization and cooperative elaboration of risk plans.

L'expérience joue un rôle crucial dans la résolution de problèmes. Dans les activités inventives de résolution de problèmes, l’expérience est composée de deux parties : l’une est le savoir-faire spécifique acquis dans la pratique de la résolution de problèmes passés, l’autre est la connaissance supplémentaire provenant d’autres domaines dans lesquels la résolution de problèmes a déjà été acquise et est utilisée pour résoudre. Cette thèse propose une nouvelle façon de résoudre des problèmes d’invention en capitalisant l’expérience tirée d’activités de résolution de problèmes antérieures. La première contribution est basée sur l'utilisation du raisonnement à partir de cas pour collecter et accéder rapidement aux expériences. La deuxième contribution consiste à proposer une nouvelle façon de classer les effets physiques basé sur l'utilisation de Wikipédia. Pour mettre en œuvre l'approche proposée dans la thèse, une application Web appelée CBRID (Raisonnement à partir de cas pour la Conception Inventive) est développée. Par ailleurs, nous avons mené une série d’expériences pour évaluer notre approche en termes d’efficacité et d’efficience. / Experience plays a crucial role in the resolution of problems. When in inventive problem solving activities, experience is composed of two parts: one is the specific know-how knowledge acquired in the practice of solving previous problems, the other is the additional knowledge from other domains where the problem solver is previously acquired and is used for problem solving. This thesis aims at proposing a new way to solve new inventive problems by capitalizing experience obtained from past problem solving activities. The first contribution is based on the use of the case-based reasoning for collecting and rapidly accessing the experiences. The second contribution consists in proposing a new way to classify the physical effects using Wikipedia. To implement the proposed approach, a web-based application called CBRID (Case-based reasoning for Inventive Design) is developed. A particular case of ''cloth hanger'' is studied to illustrate the problem solving process based on the proposed approach. In addition to that, we conducted a set of experiments to evaluate our approach in terms of effectiveness and efficiency.

La combinaison du traitement sémantique des connaissances (Semantic Processing of Knowledge) et de la modélisation des étapes de raisonnement (Modeling Steps of Reasoning), utilisés dans le domaine clinique, offrent des possibilités intéressantes, nécessaires aussi, pour l’élaboration des ontologies médicales, utiles à l'exercice de cette profession. Dans ce cadre, l'interrogation de banques de données médicales multiples, comme MEDLINE, PubMed… constitue un outil précieux mais insuffisant car elle ne permet pas d'acquérir des connaissances facilement utilisables lors d’une démarche clinique. En effet, l'abondance de citations inappropriées constitue du bruit et requiert un tri fastidieux, incompatible avec une pratique efficace de la médecine.Dans un processus itératif, l'objectif est de construire, de façon aussi automatisée possible, des bases de connaissances médicales réutilisables, fondées sur des ontologies et, dans cette thèse, nous développons une série d'outils d'acquisition de connaissances qui combinent des opérateurs d'analyse linguistique et de modélisation de la clinique, fondés sur une typologie des connaissances mises en œuvre, et sur une implémentation des différents modes de raisonnement employés. La connaissance ne se résume pas à des informations issues de bases de données ; elle s’organise grâce à des opérateurs cognitifs de raisonnement qui permettent de la rendre opérationnelle dans le contexte intéressant le praticien.Un système multi-agents d’aide à la décision clinique (SMAAD) permettra la coopération et l'intégration des différents modules entrant dans l'élaboration d'une ontologie médicale et les sources de données sont les banques médicales, comme MEDLINE, et des citations extraites par PubMed ; les concepts et le vocabulaire proviennent de l'Unified Medical Language System (UMLS).Concernant le champ des bases de connaissances produites, la recherche concerne l'ensemble de la démarche clinique : le diagnostic, le pronostic, le traitement, le suivi thérapeutique de différentes pathologies, dans un domaine médical donné.Différentes approches et travaux sont recensés, dans l’état de question, et divers paradigmes sont explorés : 1) l'Evidence Base Medicine (une médecine fondée sur des indices). Un indice peut se définir comme un signe lié à son mode de mise en œuvre ; 2) Le raisonnement à partir de cas (RàPC) se fonde sur l'analogie de situations cliniques déjà rencontrées ; 3) Différentes approches sémantiques permettent d'implémenter les ontologies.Sur l’ensemble, nous avons travaillé les aspects logiques liés aux opérateurs cognitifs de raisonnement utilisés et nous avons organisé la coopération et l'intégration des connaissances exploitées durant les différentes étapes du processus clinique (diagnostic, pronostic, traitement, suivi thérapeutique). Cette intégration s’appuie sur un SMAAD : système multi-agent d'aide à la décision. / The combination of semantic processing of knowledge and modelling steps of reasoning employed in the clinical field offers exciting and necessary opportunities to develop ontologies relevant to the practice of medicine. In this context, multiple medical databases such as MEDLINE, PubMed are valuable tools but not sufficient because they cannot acquire the usable knowledge easily in a clinical approach. Indeed, abundance of inappropriate quotations constitutes the noise and requires a tedious sort incompatible with the practice of medicine.In an iterative process, the objective is to build an approach as automated as possible, the reusable medical knowledge bases is founded on an ontology of the concerned fields. In this thesis, the author will develop a series of tools for knowledge acquisition combining the linguistic analysis operators and clinical modelling based on the implemented knowledge typology and an implementation of different forms of employed reasoning. Knowledge is not limited to the information from data, but also and especially on the cognitive operators of reasoning for making them operational in the context relevant to the practitioner.A multi-agent system enables the integration and cooperation of the various modules used in the development of a medical ontology.The data sources are from medical databases such as MEDLINE, the citations retrieved by PubMed, and the concepts and vocabulary from the Unified Medical Language System (UMLS).Regarding the scope of produced knowledge bases, the research concerns the entire clinical process: diagnosis, prognosis, treatment, and therapeutic monitoring of various diseases in a given medical field.It is essential to identify the different approaches and the works already done.Different paradigms will be explored: 1) Evidence Based Medicine. An index can be defined as a sign related to its mode of implementation; 2) Case-based reasoning, which based on the analogy of clinical situations already encountered; 3) The different semantic approaches which are used to implement ontologies.On the whole, we worked on logical aspects related to cognitive operators of used reasoning, and we organized the cooperation and integration of exploited knowledge during the various stages of the clinical process (diagnosis, prognosis, treatment, therapeutic monitoring). This integration is based on a SMAAD: multi-agent system for decision support.

Afin d'accompagner les professionnels de santé dans leur démarche clinique, plusieurs systèmes de suivi et deprise en charge médicale ont été construits et déployés dans le milieu hospitalier. Ces systèmes permettentprincipalement de collecter des données médicales sur les patients, de les analyser et de présenter les résultats dedifférentes manières. Ils représentent un appui et une aide aux professionnels de santé dans leur prise de décisionpar rapport à l'évolution de l'état de santé des patients suivis. L'utilisation de tels systèmes nécessitesystématiquement une adaptation à la fois au domaine médical concerné et au mode d'intervention. Il estnécessaire, dans un milieu hospitalier, que ces systèmes puissent s'adapter et évoluer d'une manière simple, enlimitant toute maintenance corrective ou évolutive. Ils doivent être en mesure de prendre en compte dynamiquementdes connaissances théoriques et empiriques du domaine issues des experts médicaux.Afin de répondre à ces exigences, nous avons proposé une approche pour la construction d'un système d'aide à ladécision médicale capable de s'adapter au domaine médical concerné et au mode d'intervention approprié pourassister les professionnels de santé dans leur démarche clinique. Cette approche permet notamment l'organisationde la collecte des données médicales, en tenant compte du contexte du patient, la représentation desconnaissances du domaine à base d'ontologies ainsi que leur exploitation associée aux guides de bonnes pratiqueset à l'expérience clinique.Dans la continuité des travaux précédemment réalisés au sein de notre équipe de recherche, nous avons choisid'enrichir, avec notre approche, la plateforme E-care qui est dédiée au suivi et à la détection précoce de touteanomalie de l'état de patients atteints de maladies chroniques. Nous avons pu ainsi adapter facilement la plateformeE-care aux différentes expérimentations qui sont été menées notamment dans des EPHAD de la MutualitéFrançaise en Anjou-Mayenne, au CHU de Hautepierre et au CHUV à Lausanne.Les résultats de ces expérimentations ont montré l'efficacité de l'approche proposée. L'adaptation de la plateformepar rapport au domaine et au mode d'intervention de chacune de ces expérimentations se limite à de la simpleconfiguration. De plus, l'approche proposée a suscité l'intérêt du personnel médical par rapport à l'organisation de lacollecte des données, qui tient compte du contexte du patient, et par rapport à l'exploitation des connaissancesmédicales qui apporte aux professionnels de santé une assistance pour une meilleure prise de décision. / To support health professionals in their clinical processes, several monitoring and medical care systems have beenbuilt and deployed in the hospital setting. These systems are mainly used to collect medical data on patients,analyze and present the outcomes in different ways. They represent support and assistance to health professionalsin their decision making regarding the evolution in the health status of the patients followed. The use of suchsystems always requires an adaptation to both the medical field and the mode of intervention. It is necessary, in ahospital setting, to adapt and evolve these systems in a simple manner, limiting any corrective or evolutionarymaintenance. Moreover, these systems should be able to consider dynamically the domain knowledge from medicalexperts.To meet these requirements, we proposed an approach for the construction of a medical decision support system(MDSS). This MDSS can adapt to the medical field and to the appropriate mode of intervention to assist healthprofessionals in their clinical processes. This approach allows especially the organization of the medical datacollection by taking into account the patient¿s context, the ontology-based knowledge representation of the domainand permits the exploitation of the medical guidelines and the clinical experience.In continuity of our research team¿s previous work, we chose to expand with our approach, the E-care platformwhich is dedicated to monitoring and early detection of any abnormality of the health status of patients with chronicdiseases. We were able to adapt easily the E-care platform for the various experiments that have been conducted,including EPHAD of the Mutualité Française in Anjou-Mayenne, Hautepierre hospital and Lausanne hospital(CHUV).The outcomes of these experiments have shown the effectiveness of the proposed approach. Where, the adaptationof the platform regarding to the domain and mode of intervention of each of these experiments is limited to thesimple configuration. Furthermore, the proposed approach has attracted the interest of the medical staff regardingthe organization of the medical data collection, and the exploitation of the medical knowledge which bringsassistance to the health professionals for better decision making.

In Multi-Agenten-Systemen (MAS) kooperieren und konkurrieren Agenten um ihre jeweiligen Ziele zu erreichen. Für optimierte Agenten-Interaktionen sind Kenntnisse über die aktuellen und zukünftigen Handlungen anderer Agenten (Interaktionsparter, IP) hilfreich. Bei der Ermittlung und Nutzung solcher Kenntnisse kommt dem automatischen Erkennen und Verstehen sowie der Vorhersage von Verhalten der IP auf Basis von Beobachtungen besondere Bedeutung zu. Die Dissertation beschäftigt sich mit der automatischen Bestimmung und Vorhersage von Verhalten der IP durch einen Modellierenden Agenten (MA). Der MA generiert fallbasierte, adaptive Verhaltens-Modelle seiner IP und verwendet diese zur Vorhersage ihrer Verhalten. Als Anwendungsszenario wird mit dem virtuellen Fußballspiel des RoboCup ein komplexes und populäres MAS betrachtet. Der Hauptbeitrag dieser Arbeit besteht in der Ausarbeitung, Realisierung und Evaluierung eines Ansatzes zur automatischen Verhaltens-Modellierung für ein komplexes Multi-Agenten-System. / In multi-agent-systems agents cooperate and compete to reach their personal goals. For optimized agent interactions it is helpful for an agent to have knowledge about the current and future behavior of other agents. Ideally the recognition and prediction of behavior should be done automatically. This work addresses a way of automatically classifying and an attempt at predicting the behavior of a team of agents, based on external observation only. A set of conditions is used to distinguish behaviors and to partition the resulting behavior space. From observed behavior, team specific behavior models are then generated using Case Based Reasoning. These models, which are derived from a number of virtual soccer games (RoboCup), are used to predict the behavior of a team during a new game. The main contribution of this work is the design, realization and evaluation of an automatic behavior modeling approach for complex multi-agent systems.