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Conference Papers Year : 2017

aGrUM: a Graphical Universal Model framework

Christophe Gonzales
Lionel Torti
  • Function : Author
Pierre-Henri Wuillemin

Abstract

This paper presents the aGrUM framework, a C++ library providing state-of-the-art implementations of graphical models for decision making, including Bayesian Networks, Influence Diagrams, Credal Networks, Probabilistic Relational Models. This is the result of an ongoing effort to build an efficient and well maintained open source cross-platform software, running on Linux, MacOS X and Windows, for dealing with graphical models. The framework also contains a wrapper, pyAgrum, for exploiting aGrUM within Python.
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Dates and versions

hal-01509651 , version 1 (18-04-2017)

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Christophe Gonzales, Lionel Torti, Pierre-Henri Wuillemin. aGrUM: a Graphical Universal Model framework. IEA/AIE 2017 - 30th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, Jun 2017, Arras, France. pp.171-177, ⟨10.1007/978-3-319-60045-1_20⟩. ⟨hal-01509651⟩
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