Abstract
Bayesian networks allow for a concise graphical representation of decision makers’ knowledge on an uncertain domain. However, there are no well-defined methodologies showing how to use a Bayesian network as the core of a knowledge-based system, even less if not all the features should be supported by the knowledge model. That is to say, the software, that has to be released to customers, has also to embed functionalities not based on knowledge, concerning to the information management processes closer to the world of a classical software development projects. These components of the software application have to be built according to practices and methods of Software Engineering discipline. This chapter is conceived as a guideline about how to manage and intertwine languages and techniques related to Knowledge Engineering and Software Engineering in order to build a knowledge based system supported by Bayesian networks.
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This research has been financed by the Spanish Ministry of Economy and Competitiveness under project TIN2013-46638-C3-1-P and partially supported by Data, Knowledge and Software Engineering (DKSE) research group (TIC-181) of the University of Almería.
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del Águila, I.M., del Sagrado, J. (2018). Development of Knowledge-Based Systems Which Use Bayesian Networks. In: Nalepa, G., Baumeister, J. (eds) Synergies Between Knowledge Engineering and Software Engineering. Advances in Intelligent Systems and Computing, vol 626. Springer, Cham. https://doi.org/10.1007/978-3-319-64161-4_3
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