Abstract
One of the main problems in using logic for solving problems is the high computational costs involved in inference. In this paper, we propose the use of a notion of relevance in order to cut the search space for a solution. Instead of trying to infer a formula α directly from a large knowledge base K, we consider first only the most relevant sentences in K for the proof. If those are not enough, the set can be increased until, at the worst case, we consider the whole base K.
We show how to define a notion of relevance for first-order logic with equality and analyze the results of implementing the method and testing it over more than 700 problems from the TPTP problem library.
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References
Hamscher, W., Console, L., de Kleer, J. (eds.): Readings in Model-Based Diagnosis. Morgan Kaufmann, San Francisco (1992)
Allen, J., Hendler, J., Tare, A. (eds.): Readings in Planning. Morgan Kaufmann Publishers, San Francisco (1990)
Gärdenfors, P.: Knowledge in Flux - Modeling the Dynamics of Epistemic States. MIT Press, Cambridge (1988)
Garey, M.R., Johnson, D.S.: Computers and Intractability: A Guide to the Theory of NP-Completeness. W.H. Freeman, New York (1979)
Robinson, J.A., Voronkov, A. (eds.): Handbook of Automated Reasoning. MIT Press, Cambridge (2001)
Schaerf, M., Cadoli, M.: Tractable reasoning via approximation. Artificial Intelligence 74, 249–310 (1995)
Anderson, A., Belnap, N.: Entailment: The Logic of Relevance and Necessity. Princeton University Press, Princeton (1975)
da Costa, N.C.: Calculs propositionnels pour les systémes formels inconsistants. Comptes Rendus d’Academie des Sciences de Paris 257 (1963)
Wassermann, R.: Resource-Bounded Belief Revision. PhD thesis, Institute for Logic, Language and Computation — University of Amsterdam (1999)
Finger, M., Wassermann, R.: Expressivity and control in limited reasoning. In: van Harmelen, F. (ed.) 15th European Conference on Artificial Intelligence (ECAI 2002), Lyon, France, pp. 272–276. IOS Press, Amsterdam (2002)
Epstein, R.L.: The semantic foundations of logic. Propositional Logic. Nijhoff International Philosophy Series, vol. 1. Kluwer Academic Publishers, Dordrecht (1990)
Rodrigues, O.T.: A Methodology for Iterated Information Change. PhD thesis, Imperial College, University of London (1997)
Krajewski, S.: Relatedness logic. Reports on Mathematical Logic 20, 7–14 (1986)
McCune, W., Wos, L.: Otter: The cade-13 competition incarnations. Journal of Automated Reasoning (1997)
Riani, J.: Towards an efficient inference procedure through syntax based relevance. Master’s thesis, Department of Computer Science, University of São Paulo (2004), Available at http://www.ime.usp.br/~joselyto/mestrado
Ribeiro, F.P.: otterlib – a C library for theorem proving. Technical Report RT-MAC 2002-09, Computer Science Department, University of São Paulo (2002), Available from http://www.ime.usp.br/~fr/otterlib/
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Riani, J., Wassermann, R. (2004). Using Relevance to Speed Up Inference. In: Bazzan, A.L.C., Labidi, S. (eds) Advances in Artificial Intelligence – SBIA 2004. SBIA 2004. Lecture Notes in Computer Science(), vol 3171. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28645-5_3
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DOI: https://doi.org/10.1007/978-3-540-28645-5_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23237-7
Online ISBN: 978-3-540-28645-5
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