Abstract
The expressiveness of First Order Logic (FOL) languages is severely counterbalanced by the complexity of matching formulas on a universe. Matching is an instance of the class of Constraint Satisfaction Problems (CSP), which have shown to undergo a phase transition with respect to two order parameters: constraint density and constraint tightness. This paper analyzes the problem of satisfying FOL Horn clauses in the light of these recent results. By means of an extensive experimental analysis, we show how Horn clause verification exhibits a typical phase transition with respect to the number of binary (or greater arity) predicates, and with respect to the ratio between the number of constants in the universe and the cardinality of the basic predicates extension.
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References
Anglano C., Giordana A., Lo Bello G., and Saitta L. (1998). “An Experimental Evaluation of Coevolutive Concept Learning”. In Proc. 15th Int. Conf. on Machine Learning (Madison, WI), pp. 19–27.
Cheeseman P., Kanefsky B., and Taylor W.M. (1991). “Where the Really Hard Problems Are”. In Proc. 12th Int. Joint Conf on Artificial Intelligence (Sidney, Australia), pp. 331–337.
Gent I.P., and Walsh T. (1996). “The TSP Phase Transition”. Artificial Intelligence, 88, 349–358.
Giordana A., Neri F., Saitta L., and Botta M. (1998). “Integrating Multiple Learning Strategies in First Order Logics”, Machine Learning, 27, 209–240.
Hogg T., Huberman B.A., and Williams C.P. (Eds.) (1996). Artificial Intelligence, Special Issue on Frontiers in Problem Solving: Phase Transitions and Complexity, 81 (1–2).
Hogg T., Huberman B.A., and Williams C.P. (1996). Artificial Intelligence, 81, 1–15.
Michalski R.S. (1980). “Pattern recognition as a rule-guided inductive inference”. IEEE Trans. on Pattern Analysis and Machine Intelligence, PAMI-2, 349–361.
Prosser P. (1996). “An Empirical Study of Phase Transitions in Binary Constraint Satisfaction Problems”. Artificial Intelligence, 81, 81–110.
Selman B., and Kirkpatrick S. (1996). “Critical Behavior in the Computational Cost of Satisfiability Testing”, Artificial Intelligence, 81, 273–296.
Smith B.M. (1994). “Phase Transition and the Mushy Region in Constraint Satisfaction”. In Proc. European Conf. on Artificial Intelligence (Amsterdam, The Netherlands), pp. 125–129.
Smith B.M., and Dyer M.E. (1996). “Locating the Phase Transition in Binary Constraint Satisfaction Problems”, Artificial Intelligence, 81, 155–181.
Walsh T. (1998). “The Constrainedness Knife-Edge”. In Proc. 15th National Conf. on Artificial Intelligence (Madison, Wisconsin, USA), pp. 406–411.
Williams C.P., Hogg T. (1994). “Exploiting the Deep Structure of Constraint Problems”. Artificial Intelligence, 70, 73–117.
Zhang W., and Korf R.E. (1996). “A Study of Complexity Transition on the Asymmetric Travelling Salesman Problem”. Artificial Intelligence, 81, 223–239.
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© 1999 Springer-Verlag Berlin Heidelberg
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Giordana, A., Saitta, L. (1999). On-line estimation of matching complexity in first order logic. In: Raś, Z.W., Skowron, A. (eds) Foundations of Intelligent Systems. ISMIS 1999. Lecture Notes in Computer Science, vol 1609. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0095092
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DOI: https://doi.org/10.1007/BFb0095092
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