Stochastic techniques in influence diagrams for learning bayesian network structure

Authors:
Michal Matuszak;Jacek Miękisz
Affiliations:
Faculty of Mathematics and Computer Science, Nicolaus Copernicus University, Torun, Poland;Institute of Applied Mathematics and Mechanics, University of Warsaw, Warsaw, Poland
Venue:
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part I
Year:
2012

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Abstract

The problem of learning Bayesian network structure is well known to be NP---hard. It is therefore very important to develop efficient approximation techniques. We introduce an algorithm that within the framework of influence diagrams translates the structure learning problem into the strategy optimisation problem, for which we apply the Chen's self---annealing stochastic optimisation algorithm. The effectiveness of our method has been tested on computer---generated examples.