DLV is a powerful system for Knowledge Representation and Reasoning which supports Answer Set Programming (ASP) – a logic-based programming paradigm for solving problems in a fully declarative way. DLV is currently widely used in academy, and, importantly, it has been fruitfully employed in many relevant industrial applications. Similarly to the other mainstream ASP systems, while processing an input program, in a first phase of the computation DLV eliminates the variables, thus generating a ground program which is semantically equivalent to the original one, but significantly smaller than the Herbrand Instantiation, in general. This phase, called ‘grounding’, plays a key role for the successful deployment in real-world contexts. In this work we present I-DLV, a brand new version of the intelligent grounder of DLV. While relying on the solid theoretical foundations of its predecessor, it has been completely redesigned and re-engineered, both in algorithms and data structures; it now features full support to ASP-Core-2 standard language, increased flexibility and customizability, significantly improved performance, and an extensible design that eases the incorporation of language updates and optimization techniques. I-DLV results in a stable and efficient ASP instantiator, that turns out to be a full-fledged deductive database system. We describe here the main features of I-DLV and present the results of proper experimental activities for assessing both its applicability and performance.

I-DLV: the new Intelligent Grounder of DLV -- [Extended version of the work winner of the BEST PAPER AWARD at AI*IA 2016]

CALIMERI, Francesco;FUSCA', DAVIDE;ZANGARI, JESSICA
2017

Abstract

DLV is a powerful system for Knowledge Representation and Reasoning which supports Answer Set Programming (ASP) – a logic-based programming paradigm for solving problems in a fully declarative way. DLV is currently widely used in academy, and, importantly, it has been fruitfully employed in many relevant industrial applications. Similarly to the other mainstream ASP systems, while processing an input program, in a first phase of the computation DLV eliminates the variables, thus generating a ground program which is semantically equivalent to the original one, but significantly smaller than the Herbrand Instantiation, in general. This phase, called ‘grounding’, plays a key role for the successful deployment in real-world contexts. In this work we present I-DLV, a brand new version of the intelligent grounder of DLV. While relying on the solid theoretical foundations of its predecessor, it has been completely redesigned and re-engineered, both in algorithms and data structures; it now features full support to ASP-Core-2 standard language, increased flexibility and customizability, significantly improved performance, and an extensible design that eases the incorporation of language updates and optimization techniques. I-DLV results in a stable and efficient ASP instantiator, that turns out to be a full-fledged deductive database system. We describe here the main features of I-DLV and present the results of proper experimental activities for assessing both its applicability and performance.
Artificial Intelligence; Answer Set Programming; Grounding
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11770/147760
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