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Characterization of logic program revision as an extension of propositional revision*

Published online by Cambridge University Press:  13 August 2015

NICOLAS SCHWIND
Affiliation:
Transdisciplinary Research Integration Center, 2-1-2 Hitotsubashi, Chiyoda-ku, 101-8430 Tokyo, Japan (e-mail: schwind@nii.ac.jp)
KATSUMI INOUE
Affiliation:
National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, 101-8430 Tokyo, Japan (e-mail: inoue@nii.ac.jp)

Abstract

We address the problem of belief revision of logic programs (LPs), i.e., how to incorporate to a LP P a new LP Q. Based on the structure of SE interpretations, Delgrande et al. (2008. Proc. of the 11th International Conference on Principles of Knowledge Representation and Reasoning (KR'08), 411–421; 2013b. Proc. of the 12th International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR'13), 264–276) adapted the well-known AGM framework (Alchourrón et al. 1985. Journal of Symbolic Logic 50, 2, 510–530) to LP revision. They identified the rational behavior of LP revision and introduced some specific operators. In this paper, a constructive characterization of all rational LP revision operators is given in terms of orderings over propositional interpretations with some further conditions specific to SE interpretations. It provides an intuitive, complete procedure for the construction of all rational LP revision operators and makes easier the comprehension of their semantic and computational properties. We give a particular consideration to LPs of very general form, i.e., the generalized logic programs (GLPs). We show that every rational GLP revision operator is derived from a propositional revision operator satisfying the original AGM postulates. Interestingly, the further conditions specific to GLP revision are independent from the propositional revision operator on which a GLP revision operator is based. Taking advantage of our characterization result, we embed the GLP revision operators into structures of Boolean lattices, that allow us to bring to light some potential weaknesses in the adapted AGM postulates. To illustrate our claim, we introduce and characterize axiomatically two specific classes of (rational) GLP revision operators which arguably have a drastic behavior. We additionally consider two more restricted forms of LPs, i.e., the disjunctive logic programs (DLPs) and the normal logic programs (NLPs) and adapt our characterization result to disjunctive logic program and normal logic program revision operators.

Type
Regular Papers
Copyright
Copyright © Cambridge University Press 2015 

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Footnotes

*

This is a revised and full version (including proofs of propositions given in the online appendix of the paper) of Schwind and Inoue (2013).

References

Alchourrón, C. E., Gärdenfors, P. and Makinson, D. 1985. On the logic of theory change: Partial meet contraction and revision functions. Journal of Symbolic Logic 50, 2, 510530.CrossRefGoogle Scholar
Alferes, J. J., Leite, J. A., Pereira, L. M., Przymusinska, H. and Przymusinski, T. C. 2000. Dynamic updates of non-monotonic knowledge bases. Journal of Logic Programming 45, 1–3, 4370.CrossRefGoogle Scholar
Cabalar, P. and Ferraris, P. 2007. Propositional theories are strongly equivalent to logic programs. Theory and Practice of Logic Programming 7, 6, 745759.CrossRefGoogle Scholar
Dalal, M. 1988. Investigations into a theory of knowledge base revision: Preliminary report. In Proc. of the 7th National Conference on Artificial Intelligence (AAAI'88), AAAI Press/The MIT Press, Saint Paul, MN, USA, 475479.Google Scholar
Delgrande, J. P., Peppas, P. and Woltran, S. 2013a. AGM-style belief revision of logic programs under answer set semantics. In Proc. of the 12th International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR'13), Lecture Notes in Computer Science, vol. 8148. Springer, Corunna, Spain, 264276.CrossRefGoogle Scholar
Delgrande, J. P., Schaub, T. and Tompits, H. 2007. A preference-based framework for updating logic programs. In Proceedings of the 9th International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR'07), Lecture Notes in Computer Science, vol. 4483. Springer, Tempe, AZ, USA, 7183.CrossRefGoogle Scholar
Delgrande, J. P., Schaub, T., Tompits, H. and Woltran, S. 2008. Belief revision of logic programs under answer set semantics. In Proceedings of the 11th International Conference on Principles of Knowledge Representation and Reasoning (KR'08), AAAI Press, Sydney, Australia, 411421.Google Scholar
Delgrande, J. P., Schaub, T., Tompits, H. and Woltran, S. 2009. Merging logic programs under answer set semantics. In Proceedings of the 25th International Conference on Logic Programming (ICLP'09), Lecture Notes in Computer Science, vol. 5649. Springer, Pasadena, CA, USA, 160174.Google Scholar
Delgrande, J. P., Schaub, T., Tompits, H. and Woltran, S. 2013b. A model-theoretic approach to belief change in answer set programming. ACM Transactions on Computational Logic 14, 2, 146.CrossRefGoogle Scholar
Eiter, T., Fink, M., Sabbatini, G. and Tompits, H. 2002. On properties of update sequences based on causal rejection. Theory and Practice of Logic Programming 2, 6, 711767.CrossRefGoogle Scholar
Eiter, T., Tompits, H. and Woltran, S. 2005. On solution correspondences in answer set programming. In Proc. of the 19th International Joint Conference on Artificial Intelligence (IJCAI'05), Professional Book Center, Edinburgh, Scotland, UK, 97102.Google Scholar
Inoue, K. and Sakama, C. 1998. Negation as failure in the head. Journal of Logic Programming 35, 1, 3978.CrossRefGoogle Scholar
Katsuno, H. and Mendelzon, A. O. 1989. A unified view of propositional knowledge base updates. In Proc. of the 11th International Joint Conference on Artificial Intelligence (IJCAI'89), Morgan Kaufmann, Detroit, MI, USA, 14131419.Google Scholar
Katsuno, H. and Mendelzon, A. O. 1991. On the difference between updating a knowledge base and revising it. In Proc. of the 2nd International Conference on Principles of Knowledge Representation and Reasoning (KR'91), Morgan Kaufmann, Cambridge, MA, USA, 387394.Google Scholar
Katsuno, H. and Mendelzon, A. O. 1992. Propositional knowledge base revision and minimal change. Artificial Intelligence 52, 3, 263294.CrossRefGoogle Scholar
Konieczny, S. and Pino Pérez, R. 2002. Merging information under constraints: A logical framework. Journal of Logic and Computation 12, 5, 773808.CrossRefGoogle Scholar
Liberatore, P. and Schaerf, M. 2001. Belief revision and update: Complexity of model checking. Journal of Computer and System Sciences 62, 1, 4372.CrossRefGoogle Scholar
Lifschitz, V., Pearce, D. and Valverde, A. 2001. Strongly equivalent logic programs. ACM Transactions on Computational Logic 2, 4, 526541.CrossRefGoogle Scholar
Papadimitriou, C. M. 1994. Computational Complexity. Addison-Wesley, Reading, Massachusetts.Google Scholar
Sakama, C. and Inoue, K. 2003. An abductive framework for computing knowledge base updates. Theory and Practice of Logic Programming 3, 6, 671713.CrossRefGoogle Scholar
Satoh, K. 1988. Nonmonotonic reasoning by minimal belief revision. In Proceedings of FGCS'88, OHMSHA Ltd. Tokyo and Springer-Verlag, Tokyo, Japan, 455462.Google Scholar
Schwind, N. and Inoue, K. 2013. Characterization theorems for revision of logic programs. In Proceedings of the 12th International Conference on Logic Programming and Nonmonotonic Reasoning (LPNMR'13), Lecture Notes in Computer Science, vol. 8148. Springer, Corunna, Spain, 485498.CrossRefGoogle Scholar
Slota, M. and Leite, J. 2010. On semantic update operators for answer-set programs. In Proceedings of the 19th European Conference on Artificial Intelligence (ECAI'10), vol. 215. IOS Press, Lisbon, Portugal, 957962.Google Scholar
Slota, M. and Leite, J. 2012. Robust equivalence models for semantic updates of answer-set programs. In Proceedings of the 13th International Conference on Principles of Knowledge Representation and Reasoning (KR'12), AAAI Press, Rome, Italy, 156168.Google Scholar
Slota, M. and Leite, J. 2014. The rise and fall of semantic rule updates based on SE-models. Theory and Practice of Logic Programming 14, 6, 869907.CrossRefGoogle Scholar
Turner, H. 2003. Strong equivalence made easy: Nested expressions and weight constraints. Theory and Practice of Logic Programming 3, 4–5, 609622.CrossRefGoogle Scholar
Zhang, Y. 2006. Logic program-based updates. ACM Transactions on Computational Logic 7, 3, 421472.CrossRefGoogle Scholar
Zhang, Y. and Foo, N. Y. 1997. Towards generalized rule-based updates. In Proceedings of the 15th International Joint Conference on Artificial Intelligence (IJCAI'97), Morgan Kaufmann, Nagoya, Japan, 8288.Google Scholar
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