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Abstract: . We investigate the space eciency of a Propositional Knowledge Representation (PKR) formalism. Informally, the space eciency of a formalism F in representing a certain piece of knowledge , is the size of the shortest formula of F that represents . In this paper we assume that knowledge is either a set of propositional interpretations or a set of formulae (theorems). We provide a formal way of talking about the relative ability of PKR formalisms to compactly represent a set of models ... (Update)
Context of citations to this paper: More
...worst cases for the space needed for compiling Artificial Intelligence 29 problems. The formal tools we built have been used in [9] for investigating the space efficiency of a propositional Knowledge Representation formalism. Informally, the space efficiency of a formalism F...
.... any propositional formula into a 5 A more general notion of space efficiency (model preservation for polysize reductions) exists [Cadoli et al. 1996] , but we do not need its full generality here. 6 We stress here that we do not require that there exists a function that...
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BibTeX entry: (Update)
M. Cadoli, F. Donini, P. Liberatore, and M. Schaerf. Comparing space efficiency of propositional knowledge representation formalisms. In Proceedings of the Fifth International Conference on the Principles of Knowledge Representation and Reasoning (KR-96), pages 364--373, 1996. http://citeseer.ist.psu.edu/article/cadoli96comparing.html More
@incollection{ cadoli96comparing,
author = "Marco Cadoli and Francesco M. Donini and Paolo Liberatore and Marco Schaerf",
title = "Comparing Space Efficiency of Propositional Knowledge Representation Formalisms",
booktitle = "{KR}'96: Principles of Knowledge Representation and Reasoning",
publisher = "Morgan Kaufmann",
address = "San Francisco, California",
editor = "Luigia Carlucci Aiello and Jon Doyle and Stuart Shapiro",
pages = "364--374",
year = "1996",
url = "citeseer.ist.psu.edu/article/cadoli96comparing.html" }
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