A carregar...
Publicação
Probabilistic constraint reasoning
| Nome: | Descrição: | Tamanho: | Formato: | |
|---|---|---|---|---|
| 7.3 MB | Adobe PDF |
Orientador(es)
Resumo(s)
The continuous constraint paradigm has been often used to model safe reasoning in applications where uncertainty arises. Constraint propagation propagates intervals of uncertainty among the variables of the problem, eliminating values that do not belong to any solution. However, constraint
programming is very conservative: if initial intervals are wide (reflecting large uncertainty), the obtained safe enclosure of all consistent scenarios may be inadequately wide for decision support. Since all scenarios are considered equally likely, insufficient pruning leads to great inefficiency if some costly decisions may be justified by very unlikely scenarios. Even
when probabilistic information is available for the variables of the problem,
the continuous constraint paradigm is unable to incorporate and reason with such information. Therefore, it is incapable of distinguishing between different scenarios, based on their likelihoods.
This thesis presents a probabilistic continuous constraint paradigm that
associates a probabilistic space to the variables of the problem, enabling
probabilistic reasoning to complement the underlying constraint reasoning.
Such reasoning is used to address probabilistic queries and requires the computation of multi-dimensional integrals on possibly non linear integration regions. Suitable algorithms for such queries are developed, using safe or approximate
integration techniques and relying on methods from continuous constraint programming in order to compute safe covers of the integration region.
The thesis illustrates the adequacy of the probabilistic continuous constraint
framework for decision support in nonlinear continuous problems with uncertain
information, namely on inverse and reliability problems, two different
types of engineering problems where the developed framework is particularly
adequate to support decision makers.
Descrição
Dissertação apresentada para obtenção do Grau de Doutor em Engenharia Informática, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia