22 resultados para Differential Inclusions with Constraints


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Dissertação para obtenção do Grau de Mestre em Lógica Computacional

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This work studies the combination of safe and probabilistic reasoning through the hybridization of Monte Carlo integration techniques with continuous constraint programming. In continuous constraint programming there are variables ranging over continuous domains (represented as intervals) together with constraints over them (relations between variables) and the goal is to find values for those variables that satisfy all the constraints (consistent scenarios). Constraint programming “branch-and-prune” algorithms produce safe enclosures of all consistent scenarios. Special proposed algorithms for probabilistic constraint reasoning compute the probability of sets of consistent scenarios which imply the calculation of an integral over these sets (quadrature). In this work we propose to extend the “branch-and-prune” algorithms with Monte Carlo integration techniques to compute such probabilities. This approach can be useful in robotics for localization problems. Traditional approaches are based on probabilistic techniques that search the most likely scenario, which may not satisfy the model constraints. We show how to apply our approach in order to cope with this problem and provide functionality in real time.

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Informática

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The basic motivation of this work was the integration of biophysical models within the interval constraints framework for decision support. Comparing the major features of biophysical models with the expressive power of the existing interval constraints framework, it was clear that the most important inadequacy was related with the representation of differential equations. System dynamics is often modelled through differential equations but there was no way of expressing a differential equation as a constraint and integrate it within the constraints framework. Consequently, the goal of this work is focussed on the integration of ordinary differential equations within the interval constraints framework, which for this purpose is extended with the new formalism of Constraint Satisfaction Differential Problems. Such framework allows the specification of ordinary differential equations, together with related information, by means of constraints, and provides efficient propagation techniques for pruning the domains of their variables. This enabled the integration of all such information in a single constraint whose variables may subsequently be used in other constraints of the model. The specific method used for pruning its variable domains can then be combined with the pruning methods associated with the other constraints in an overall propagation algorithm for reducing the bounds of all model variables. The application of the constraint propagation algorithm for pruning the variable domains, that is, the enforcement of local-consistency, turned out to be insufficient to support decision in practical problems that include differential equations. The domain pruning achieved is not, in general, sufficient to allow safe decisions and the main reason derives from the non-linearity of the differential equations. Consequently, a complementary goal of this work proposes a new strong consistency criterion, Global Hull-consistency, particularly suited to decision support with differential models, by presenting an adequate trade-of between domain pruning and computational effort. Several alternative algorithms are proposed for enforcing Global Hull-consistency and, due to their complexity, an effort was made to provide implementations able to supply any-time pruning results. Since the consistency criterion is dependent on the existence of canonical solutions, it is proposed a local search approach that can be integrated with constraint propagation in continuous domains and, in particular, with the enforcing algorithms for anticipating the finding of canonical solutions. The last goal of this work is the validation of the approach as an important contribution for the integration of biophysical models within decision support. Consequently, a prototype application that integrated all the proposed extensions to the interval constraints framework is developed and used for solving problems in different biophysical domains.

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This article is a short introduction on how to use Modellus (a computer package that is freely available on the Internet and used in the IOP Advancing Physics course) to build physics games using Newton’s laws, expressed as differential equations. Solving systems of differential equations is beyond most secondary-school or first-year college students. However, with Modellus, the solution is simply the output of the usual physical reasoning: define the force law, compute its magnitude and components, use it to obtain the acceleration components, then the velocity components and, finally, use the velocity components to find the coordinates.

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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e Computadores

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Cretaceous Research 30 (2009) 575–586

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Trabalho apresentado no âmbito do European Master in Computational Logics, como requisito parcial para obtenção do grau de Mestre em Computational Logics

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Dissertação apresentada para obtenção do Grau de Doutor em Ciências do Ambiente, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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Modification of natural areas by human activities mostly has a negative impact on wildlife by increasing the geographical and ecological overlap between people and animals. This can result in escalating levels of competition and conflict between humans and wildlife, for example over crops. However, data on specific crops and crop parts that are unattractive to wildlife yet important for human livelihoods are surprisingly scarce, especially considering their potential application to reducing crop damage by wildlife. Here we examine the co-utilization of a nationally important and spatially abundant cash crop, cashew Anacardium occidentalis, by people and chimpanzees Pan troglodytes verus inhabiting a forested–agricultural matrix in Cantanhez National Park in Guinea-Bissau. In this Park people predominantly harvest the marketable cashew nut and discard the unprofitable fruit whereas chimpanzees only consume the fruit. Local farmers generally perceive a benefit of raiding by chimpanzees as they reportedly pile the nuts, making harvesting easier. By ensuring that conflict levels over crops, especially those with high economic importance, remain low, the costs of living in proximity to wildlife can potentially be reduced. Despite high levels of deforestation associated with cashew farming, these findings point to the importance of cashew as a low-conflict crop in this area.

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica

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Dissertation toobtaina Master of Science degree in Bioorganics