Boosting MUC extraction in unsatisfiable constraint networks

One very fertile domain of applied Artificial Intelligence is constraint solving technologies. Especially, constraint networks that concern problems that can be represented using discrete variables, together with constraints on allowed instantiation values for these variables. Every solution to a co...

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Veröffentlicht in:	Applied intelligence (Dordrecht, Netherlands) Netherlands), 2014-12, Vol.41 (4), p.1012-1023
Hauptverfasser:	Grégoire, Éric, Lagniez, Jean-Marie, Mazure, Bertrand
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithmics. Computability. Computer arithmetics Algorithms Applied sciences Artificial Intelligence Boolean Computation Computer Science Computer science control theory systems Data processing. List processing. Character string processing Exact sciences and technology Experimentation Expert systems Intelligence Machines Manufacturing Mathematical models Mechanical Engineering Memory organisation. Data processing Networks Processes Software State of the art Theoretical computing Variables
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