Leaning the Structure of Bayesian Networks Using Learning Automata
Subject Areas : electrical and computer engineeringM. R. Mollakhalili Meybodi 1 , M. R. Meybodi 2
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Keywords: Learning automata Bayesian network structure learning,
Abstract :
The structure of a Bayesian network represents a set of conditional independence relations that hold in the domain. Learning the structure of the Bayesian network model that represents a domain can reveal in sights into its underlying causal structure. Automatically learning the graph structure of a Bayesian network is a challenge pursued within artificial intelligence studies. In this paper, a new algorithm based on learning automata is proposed for learning the structure of the Bayesian networks. In this algorithm, automata is used as a tool for searching in structure’s space (DAG’s space) of the Bayesian networks. The mathematical behavior of the proposed algorithm is studied.
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