Abstract
CR-Prolog is an extension of the knowledge representation language A-Prolog. The extension is built around the introduction of consistency-restoring rules (cr-rules for short), and allows an elegant formalization of events or exceptions that are unlikely, unusual, or undesired. The flexibility of the language has been extensively demonstrated in the literature, with examples that include planning and diagnostic reasoning.
In this paper we present the design of an inference engine for CR-Prolog that is efficient enough to allow the practical use of the language for medium-size applications. The capabilities of the inference engine have been successfully demonstrated with experiments on an application independently developed for use by NASA.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Balduccini, M.: USA-Smart: Improving the Quality of Plans in Answer Set Planning. In: Jayaraman, B. (ed.) PADL 2004. LNCS, vol. 3057, pp. 135–147. Springer, Heidelberg (2004)
Balduccini, M.: Computing Answer Sets of CR-Prolog Programs. Technical report, Texas Tech University (2006), http://krlab.cs.ttu.edu/~marcy/bib.php
Balduccini, M., Gelfond, M.: Logic Programs with Consistency-Restoring Rules. In: Doherty, P., McCarthy, J., Williams, M.-A. (eds.) International Symposium on Logical Formalization of Commonsense Reasoning, AAAI 2003 Spring Symposium Series, Mar. 2003, pp. 9–18 (2003)
Balduccini, M., Gelfond, M., Nogueira, M.: Answer Set Based Design of Knowledge Systems. Annals of Mathematics and Artificial Intelligence (2006)
Baral, C.: Knowledge Representation, Reasoning, and Declarative Problem Solving, Jan. 2003. Cambridge University Press, Cambridge (2003)
Baral, C., Gelfond, M., Rushton, N.: Probabilistic reasoning with answer sets. Journal of Theory and Practice of Logic Programming (TPLP) (submitted) (2005)
Gelfond, M.: Representing Knowledge in A-Prolog. In: Kakas, A.C., Sadri, F. (eds.) Computational Logic: Logic Programming and Beyond. LNCS (LNAI), vol. 2408, pp. 413–451. Springer, Heidelberg (2002)
Gelfond, M., Lifschitz, V.: Classical negation in logic programs and disjunctive databases. New Generation Computing, 365–385 (1991)
Kolvekar, L.: Developing an Inference Engine for CR-Prolog with Preferences. Master’s thesis, Texas Tech University (Dec. 2004)
Nogueira, M.: Building Knowledge Systems in A-Prolog. PhD thesis, University of Texas at El Paso (May 2003)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer Berlin Heidelberg
About this paper
Cite this paper
Balduccini, M. (2007). cr-models: An Inference Engine for CR-Prolog. In: Baral, C., Brewka, G., Schlipf, J. (eds) Logic Programming and Nonmonotonic Reasoning. LPNMR 2007. Lecture Notes in Computer Science(), vol 4483. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72200-7_4
Download citation
DOI: https://doi.org/10.1007/978-3-540-72200-7_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72199-4
Online ISBN: 978-3-540-72200-7
eBook Packages: Computer ScienceComputer Science (R0)