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Summary: BUILDING KNOWLEDGE-BASED SYSTEMS
BY CREDAL NETWORKS: A TUTORIAL
Alberto Piatti1
, Alessandro Antonucci2
and Marco Zaffalon2
1
Mathematical and Physical Sciences Unit (SMF),
University of Applied Sciences and Arts of Southern Switzerland (SUPSI),
Galleria 2, CH-6928 Manno (Lugano), Switzerland
2
Istituto Dalle Molle di Studi sull'Intelligenza Artificiale (IDSIA),
Galleria 2, CH-6928 Manno (Lugano), Switzerland
Abstract
Knowledge-based systems are computer programs achieving expert-level compe-
tence in solving problems for specific task areas. This chapter is a tutorial on the
implementation of this kind of systems in the framework of credal networks. Credal
networks are a generalization of Bayesian networks where credal sets, i.e., closed con-
vex sets of probability measures, are used instead of precise probabilities. This allows
for a more flexible model of the knowledge, which can represent ambiguity, contrast
and contradiction in a natural and realistic way. The discussion guides the reader
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