A branch-and-bound algorithm for MDL learning Bayesian networks
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
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Automation of software configuration management is an important practical problem. Any automated tool must work from some specifications of correct or desired configurations. This report introduces a language for describing acceptable configurations of common systems, so that automated management is possible. The proposed language is declarative, while at the same time there are efficient algorithms for modifying a system to conform to a specification in many cases of practical importance.