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Thesis on the Bayesian networks.

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Title: Evolutionary approach for Bayesian networks structure learning

Authors: Alain Delaplace

Level:  Advanced

Categories: Thesis

Abstract:

In this thesis, we propose a study of the problem of learning the structure of a bayesian network
through the use of evolutionary methods.We first designed a genetic algorithm to search
the space of structures before establishing various strategies aiming at improving the performances
of this algorithm. We consequently developed a search strategy aiming at exploiting
the properties of the space of completed partially oriented graphs using a sequential niching
principle which we later hybridized with an island model scheme. Another method defines a
distribution probability over the mutation operations which are applied to the individuals and
that is a function of the qualitative results of previously applied operations.
In this thesis, we propose a study of the problem of learning the structure of a bayesian network through the use of evolutionary methods.We first designed a genetic algorithm to search the space of structures before establishing various strategies aiming at improving the performances of this algorithm. We consequently developed a search strategy aiming at exploiting the properties of the space of completed partially oriented graphs using a sequential niching principle which we later hybridized with an island model scheme. Another method defines a distribution probability over the mutation operations which are applied to the individuals and that is a function of the qualitative results of previously applied operations.

Langages: French

Files: *.pdf