University, Diss., 2003--Jena.

Techn. University, Diss., 2001--Berlin.

Techn. University, Diss., 2004--Berlin.

Universiẗat, Diss., 2000--Saarbrücken.

Universiẗat, Diss., 2006--Paderborn.

Research in mobile ad-hoc networks has focused on situations in whichnodes have no control over their movements. We investigate animportant but overlooked domain in which nodes do have controlover their movements. Reinforcement learning methods can be used tocontrol both packet routing decisions and node mobility, dramaticallyimproving the connectivity of the network. We first motivate theproblem by presenting theoretical bounds for the connectivityimprovement of partially mobile networks and then present superiorempirical results under a variety of different scenarios in which themobile nodes in our ad-hoc network are embedded with adaptive routingpolicies and learned movement policies.

Most Artificial Intelligence (AI) work can be characterized as either ``high-level'' (e.g., logical, symbolic) or ``low-level'' (e.g., connectionist networks, behavior-based robotics). Each approach suffers from particular drawbacks. High-level AI uses abstractions that often have no relation to the way real, biological brains work. Low-level AI, on the other hand, tends to lack the powerful abstractions that are needed to express complex structures and relationships. I have tried to combine the best features of both approaches, by building a set of programming abstractions defined in terms of simple, biologically plausible components. At the ``ground level'', I define a primitive, perceptron-like computational unit. I then show how more abstract computational units may be implemented in terms of the primitive units, and show the utility of the abstract units in sample networks. The new units make it possible to build networks using concepts such as long-term memories, short-term memories, and frames. As a demonstration of these abstractions, I have implemented a simulator for ``creatures'' controlled by a network of abstract units. The creatures exist in a simple 2D world, and exhibit behaviors such as catching mobile prey and sorting colored blocks into matching boxes. This program demonstrates that it is possible to build systems that can interact effectively with a dynamic physical environment, yet use symbolic representations to control aspects of their behavior.

Thèse univ.--Sc.--Paris 6, 1971. / Bibliogr.

Agent-based modeling (ABM) is a modeling and simulation paradigm well-suited to social systems where agents interact and have some degree of autonomy. In their most basic sense, ABMs consist of agents (generally, individuals) interacting in an environment according to a set of behavioural rules. The foundational premise and the conceptual depth of ABM is that simple rules of individual behaviour will aggregate to illuminate complex and/or emergent group-level phenomena that are not specifically encoded by the modeler and that cannot be predicted or explained by the agent-level rules. In essence, ABM has the potential to reveal a whole that is greater than the sum of its parts. In this thesis, ABMs have been utilized as a modeling framework for three specific healthcare applications, including: • the development of an ABM of an emergency department within a hospital allowing the modeling of contact-based infectious diseases such as influenza, and simulating various mitigation strategies; • the development of an ABM to model the effectiveness of a real-time location system (RTLS) using radio frequency identification (RFID) in an emergency department, used for patient tracking as one measure of hospital efficiency; and, • the development of an ABM to test strategies for disaster preparedness (high volume, high risk patients) using a fictitious case of zombies in an emergency department. Although each ABM was purposeful and meaningful for its custom application, each ABM also represented an iteration toward the development of a generic ABM framework. Finally, a thorough critique of ABMs and the modifications required to create a more robust framework are provided. / February 2016

Orientador: Tania Ruiz / Banca: Elen Rose Lodeiro Castanheira / Banca: Gilberto Luppi / Resumo: O Agente Comunitário de Saúde (ACS), considerado protagonista do atual cenário de reorganização da atenção primária à saúde no Brasil, é o elemento de integração entre as equipes e a comunidade onde reside. O envelhecimento populacional faz com que saber entender e relacionar-se com os idosos se torne um desafio para esse personagem na boa execução de suas funções. Assim, é fundamental sabermos o que os ACS pensam e conhecem sobre o idoso e sobre o envelhecimento. Nosso estudo tem os objetivos de descrever e analisar o perfil sociodemográfico, a experiência de convivência e trabalho com idosos, as atitudes em relação à velhice e os conhecimentos que os ACS de Marília-SP têm sobre o envelhecimento. Foi realizado um estudo transversal, de caráter descritivo onde se entrevistaram os 213 agentes comunitários das 12 Unidades Básicas de Saúde (UBS) e 29 Unidades de Saúde da Família (USF) de Marília. Os dados foram coletados através de um questionário sociodemográfico e dois instrumentos: uma escala de atitudes em relação à velhice e um questionário para avaliar conhecimentos gerontológicos. Os resultados mostraram que o quadro de ACS de Marília é formado predominantemente por adultos jovens, do sexo feminino, casados, com mais de 12 anos de escolaridade e inseridos nesta atividade há mais de 6 anos. Verificamos que a maioria dos profissionais relatou experiência com grupo de idosos e convivência intra-domiciliar com pessoas desta faixa etária, porém menos da metade referiu capacitação no tema "envelhecimento". Comparando UBS e USF, nas primeiras, onde a população idosa é maior, os ACS são de faixa etária mais alta, têm mais tempo de trabalho, maior convivência intra-domiciliar com idosos, mais experiência com grupos de idosos e referem mais capacitação em envelhecimento. Quanto às atitudes em relação à velhice, as avaliações ... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Community Health Agents (CHAs), considered to be protagonists in the present scenario of primary health care reorganization in Brazil, are the elements of integration between the teams and the community where they reside. Population ageing makes knowing, understanding and relating to the elderly a challenge to these players in the performance of their duties. Hence, it is fundamental to know what CHAs think and know about the elderly and ageing. Our study aimed at describing and analyzing the socio-demographic profile of CHAs, their experience of being and working with the elderly, their attitudes in relation to old age and the knowledge that CHAs from Marília-SP have about ageing. A cross-sectional descriptive study was conducted in which the 213 community agents from the 12 primary care units (UBS) and the 29 Family Health Units (UFS) in Marília were interviewed. Data were collected by means of a socio-demographic questionnaire and two instruments: a scale of attitudes in relation to old age and a questionnaire to evaluate gerontological knowledge. Results showed that the team of CHAs predominantly comprises young adults who are married, have attended school for longer than 12 years and have worked in this activity for over 6 years. It was observed that most of the professionals reported to have experience with the group of elderly people as well as intradomiciliary contact with individuals at that age range. However, fewer than half of the CHAs reported to have been trained on the topic of "ageing". By comparing UBSs and USFs, in the former, where the elderly population is larger, the CHAs are older, have been working longer, have more intradomicilary contact with the elderly and more experience with elderly groups. They also report to have been better trained on ageing. Concerning attitudes in relation to old age, the CHA's positive evaluations occurred particularly in ... (Complete abstract click electronic access below) / Mestre