Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Cooperative Coevolutionary Genetic Algorithm for Learning Bayesian
  Network Structures   We propose a cooperative coevolutionary genetic algorithm for learning
Bayesian network structures from fully observable data sets. Since this problem
can be decomposed into two dependent subproblems, that is to find an ordering
of the nodes and an optimal connectivity matrix, our algorithm uses two
subpopulations, each one representing a subtask. We describe the empirical
results obtained with simulations of the Alarm and Insurance networks. We show
that our algorithm outperforms the deterministic algorithm K2.

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The categories of this paper are: dg-ga
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The categories of this paper are: atom-ph
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The categories of this paper are: plasm-ph
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The categories of this paper are: math-ph
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The categories of this paper are: supr-con
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The categories of this paper are: hep-ph
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The categories of this paper are: hep-lat
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The categories of this paper are: physics
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The categories of this paper are: nucl-th
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The categories of this paper are: gr-qc
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The categories of this paper are: q-fin
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The categories of this paper are: solv-int
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The categories of this paper are: adap-org
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The categories of this paper are: cmp-lg
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The categories of this paper are: comp-gas
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The categories of this paper are: eess