Nos travaux de recherches sont des travaux supports pour les gestionnaires de l’hôpital Robert Pax de Sarreguemines, et plus généralement de tout centre hospitalier pour développer des approches centrées sur le patient. Nous nous sommes inspirés des approches centrées sur le produit issues du domaine industriel qui ont été proposées pour répondre aux exigences croissantes de gestion des produits dans un environnement de plus en plus incertain. Par analogie, les systèmes de production de soins centrés patient peuvent être assimilés aux systèmes de production de biens centrés produit. Cependant, il ne faut pas perdre de vue la spécificité des systèmes de production de soins : le facteur humain. Cette spécificité est à l’origine de leur caractère complexe, aléatoire et imprévisible. Par ailleurs, les approches de pilotage, que ce soit dans le milieu industriel ou hospitalier, sont majoritairement des modèles mathématiques et des modèles de simulation utilisant une approche de gestion centrée sur une ou plusieurs ressources considérées comme critiques. C’est pourquoi il nous a paru judicieux d’opter pour une approche centrée patient basée sur le paradigme multi-agents. Nous proposons alors, un système multi-agents de pilotage réactif dynamique et distribué centré patient du parcours patient au sein des systèmes hospitaliers. L’alternative que nous proposons consiste à utiliser une approche centrée patient et basée sur les agents permettant de minimiser les délais d’attente, ainsi que la durée de séjour, et par conséquent les coûts des soins, tout en assurant un soin de qualité pour l’ensemble des patients et une meilleure gestion des ressources hospitalières / Through our research, we offer a support tool for the managers in Robert Pax hospital in Sarreguemine (France), and more generally any hospital center wishing to develop a patient centered approach. We were inspired by « product centered » approaches emerging from industrial domain which were proposed to answer the increasing requirements of products management. By analogy, health care systems patient centered can be assimilated to production systems product centered. However, it is important not to lose sight of the specificities of health care systems which is the human factor. This specificity makes this system complex, random and unpredictable. Besides, the approaches used in industrial or hospital environment, are mainly mathematical models and simulation approaches centered on one ore several resources categorized as critical. In that sense, it seemed judicious to choose a patient centered approach based on a multi-agent paradigm. We proposed a Reactive multi-agent control system of the patient flow in healthcare system. The proposed alternative is a patient centered approach allowing to minimize the patients waiting time and the length of their stay and consequently the care costs. The proposed approach also ensures the care quality and an optimal use of the hospital resources

Made available in DSpace on 2016-08-17T14:53:24Z (GMT). No. of bitstreams: 1 Dissertacao Rafael de Souza.pdf: 5581665 bytes, checksum: 4edbe8b1f2b84008b5129a93038f2fee (MD5) Previous issue date: 2013-03-04 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / In this work, we applied the technology of Multi-Agent Systems (MAS) in the capital market, i.e., the stock market, specifically in Bolsa de Mercadorias e Futuros de São Paulo (BM&FBovespa). The research focused mainly on negotiation protocols and learning of investors agents. Within the Stock Exchange competitive field, the development of an agent that could learn to negotiate, could become differential for investors who wish to increase their profits. The decision-making based on historical data is motivation for further research in the same direction, however, we sought a different approach with regard to the representation of the states of q-learning algorithm. The reinforcement learning, in particular q-learning, has been shown to be effective in environments with various historical data and seeking reward decisions with positive results. That way it is possible to apply in the purchase and sale of shares, an algorithm that rewards the profit and punishes the loss. Moreover, to achieve their goals agents need to negotiate according to specific protocols of stock exchange. Therefore, endeavor was also the specifications of the rules of negotiation between agents that allow the purchase and sale of shares. Through the exchange of messages between agents, it is possible to determine how the trading will occur and facilitate communication between them, because it sets a standard of how it will happen. Therefore, in view of the specification of negotiation protocols based on q-learning, this research has been the modeling of intelligent agents and models of learning and negotiation required for decision making entities involved. / Neste trabalho, aplicou-se a tecnologia de Sistemas MultiAgente (SMA) no mercado de capitais, isto é, na Bolsa de Valores, especificamente na Bolsa de Mercadorias e Futuros de São Paulo (BM&FBovespa). A pesquisa concentrou-se principalmente nos protocolos de negociação envolvidos e na aprendizagem dos agentes investidores. Dentro do cenário competitivo da Bolsa de Valores, o desenvolvimento de um agente que aprendesse a negociar poderia se tornar diferencial para os investidores que desejam obter lucros cada vez maiores. A tomada de decisão baseada em dados históricos é motivação para outras pesquisas no mesmo sentido, no entanto, buscou-se uma abordagem diferenciada no que diz respeito à representação dos estados do algoritmo de aprendizagem-q. A aprendizagem por reforço, em especial a aprendizagem-q, tem demonstrado ser eficiente em ambientes com vários dados históricos e que procuram recompensar decisões com resultados positivos. Dessa forma é possível aplicar na compra e venda de ações, um algoritmo que premia o lucro e pune o prejuízo. Além disso, para conseguir alcançar seus objetivos os agentes precisam negociar de acordo com os protocolos específicos da bolsa de valores. Sendo assim, procurou-se também as especificações das regras de negociação entre os agentes que permitirão a compra e venda de títulos da bolsa. Através da troca de mensagens entre os agentes, é possível determinar como a negociação ocorrerá e facilitará comunicação entre os mesmos, pois fica padronizada a forma como isso acontecerá. Logo, tendo em vista as especificações dos protocolos de negociação baseados em aprendizagem-q, tem-se nesta pesquisa a modelagem dos agentes inteligentes e os modelos de aprendizagem e negociação necessários para a tomada de decisão das entidades envolvidas.