BN-Tools: A Software Toolkit for Experimentation in BBNs

Benjamin Perry and Julie Stilson, Kansas State University

In this paper, I describe BN-Tools, an open-source, Java-based library for experimental research in Bayesian belief networks that implements several popular algorithms for estimation (approximate inference) and learning along with a graphical user interface for interactive display and editing of graphical models. Included in the discussion are our implementations of the Lauritzen-Spiegelhalter algorithm, an adaptive importance sampling algorithm, the K2 learning algorithm, and two genetic algorithm wrappers.

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