Knowledge compilation and theory approximation

作者: Bart Selman , Henry Kautz

DOI: 10.1145/226643.226644

关键词:

摘要: Computational efficiency is a central concern in the design of knowledge representation systems. In order to obtain efficient systems, it has been suggested that one should limit form statements base or use an incomplete inference mechanism. The former approach often too restrictive for practical applications, whereas latter leads uncertainty about exactly what can and cannot be inferred from base. We present third alternative, which given general language translated (compiled) into tractable form—allowing subsequent query answering.We show how propositional logical theories compiled Horn approximate original information. approximations bound theory below above terms strength. procedures are extended other languages (for example, binary clauses) first-order case. Finally, we demonstrate generality our by compiling concept descriptions frame-based form.

参考文章(69)
Marco Cadoli, Marco Schaerf, Approximation in Concept Description Languages. principles of knowledge representation and reasoning. pp. 330- 341 ,(1992)
Bart Selman, Henry Kautz, Knowledge compilation using horn approximations national conference on artificial intelligence. pp. 904- 909 ,(1991)
Marco Cadoli, Semantical and computational aspects of horn approximations international joint conference on artificial intelligence. pp. 39- 44 ,(1993)
Werner Nutt, Maurizio Lenzerini, Daniele Nardi, Francesco M. Donini, The Complexity of Concept Languages. principles of knowledge representation and reasoning. pp. 151- 162 ,(1991)
Goran Gogic, Christos H. Papadimitriou, Martha Sideri, Incremental recompilation of knowledge (extended abstract) national conference on artificial intelligence. pp. 922- 927 ,(1994)
Alvaro Del Val, An analysis of approximate knowledge compilation international joint conference on artificial intelligence. pp. 830- 836 ,(1995)
Bart Selman, Henry Kautz, An empirical evaluation of knowledge compilation by theory approximation national conference on artificial intelligence. pp. 155- 161 ,(1994)
Bart Selman, Tractable default reasoning University of Toronto. ,(1992)
Dale Schuurmans, Russell Greiner, Learning Useful Horn Approximations. principles of knowledge representation and reasoning. pp. 383- 392 ,(1992)
Dana S. Nau, Kutluhan Erol, V. S. Subrahmanian, On the complexity of domain-independent planning national conference on artificial intelligence. pp. 381- 386 ,(1992)