Abstract
We propose to model integrated reflective and reactive reasoning by massively parallel nonmonotonic model generation. To this end, a finite representation of models of normal logic programs is given, which is adapted to the interpretations typically produced by the meaning function Tp. By simulating Tp on top of this representation, only finite representations of (possibly infinite) interpretations are processed. These representations are significantly shorter than by using related approaches. Our work overcomes typical problems of model generation and results in a tractable method, and, thereby, enables the integrated reflective and reactive reasoning we propose.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
References
F. Baader and J. H. Siekmann. Unification theory. In: Handbook of Logic in AI and Logic Programming, Vol. 2. Oxford Science Publications, 1994.
F. Bry and A. Yahya. Minimal model generation with positive unit hyperresolution tableaux. Technical Report PMS-FB-1996-1, LMU Munic, 96.
R. Caferra and N. Peltier. Decision procedures using model building techniques. In Computer Science Logic, pages 130–144. Springer, LNCS 1092, 1995.
R. Caferra and N. Peltier. Model building and interactive theory discovery. In TABLEAUX 95, volume 918 of LNAI, pages 154–168. Springer, 1995.
D. Chan. Constructive negation based on the completed database. In Proceedings of the International Conference on Logic Programming, pages 111–125, 1988.
K. L. Clark. Negation as failure. In H. Gallaire and J. Minker, editors, Logic and Databases, pages 293–322. Plenum, New York, NY, 1978.
M. Falaschi, G. Levi, M. Martelli, and C. Palamidessi. A new declarative semantics for logic languages. In R. A. Kowalski and K. R. Bowen, editors, Proceedings of the International Conference and Symposium on Logic Programming, pages 993–10005, MIT press, 1988.
M. Falaschi, G. Levi, M. Martelli, and C. Palamidessi. A model-theoretic reconstruction of the operational semantics of logic programs. Information and Computation, 102(1): 86–113, 1993.
C. Fermueller and A. Leitsch. Hyperresolution and automated model building. Journal of Logic and Computation, 6(2): 173–203, 1996.
M. Fitting. Metric methods—three examples and a theorem. Journal of Logic Programming, 21(3): 113–127, November 1994.
M. Fujita, R. Hasegawa, M. Koshimura, and H. Fujita. Model generation theorem provers on a parallel inference machine. In Proceedings of the International Conference on Fifth Generation Computer Systems, 1992.
M. Fujita, J. K. Slaney, and R. Hasegawa. New results in mathematics by a parallel theorem prover on the parallel inference machine. ICOT, 1992.
M.M. Gupta and D.H. Rao. On the principles of fuzzy neural networks. Fuzzy Sets and Systems, 61: 1–18, 1994.
S. Hölldobler. Automated inferencing and connectionist models. Technical Report AIDA-93-06, Intellektik, Informatik, TH Darmstadt, 1993. (Postdoctoral Thesis).
S. Hölldobler and Y. Kalinke. Towards a massively parallel computational model for logic programming. In Proceedings of the ECAI94 Workshop on Combining Symbolic and Connectionist Processing, pages 68–77. ECCAI, 1994.
K. Inoue, M. Koshimura, and R. Hasegawa. Embedding negation as failure into a model generation theorem prover. In D. Kapur, editor, Proceedings of the Conference on Automated Deduction, pages 400–415. Springer, 1992.
P. N. Johnson-Laird and R. M. J. Byrne. Deduction. Lawrence Erlbaum Associates, Hove and London (UK), 1991.
Y. Kalinke. Using connectionist term representation for first-order deduction—a critical view. In F. Maire, R. Hayward, and J. Diederich, editors, Connectionist Systems for Knowledge Representation Deduction. Queensland University of Technology, 1997. CADE-14 Workshop, Townsville, Australia.
T. E. Lange and M. G. Dyer. High-level inferencing in a connectionist network. Connection Science, 1: 181–217, 1989.
J. W. Lloyd. Foundations of Logic Programming. Springer, 1987.
R. Manthey and F. Bry. SATCHMO: A theorem prover implemented in Prolog. In E. Lusk and R. Overbeek, editors, Proceedings of the Conference on Automated Deduction, volume 310 of Lecture Notes in Computer Science, pages 415–434. Springer, 1988.
H. J. Ohlbach. Abstraction tree indexing for terms. In L. C. Aiello, editor, Proceedings of the European Conference on Artificial Intelligence, pages 479–484, 1990.
N. Peltier. Simplifying and generalizing formulae in tableaux. Pruning the search space and building models. In TABLEAUX 97, volume 1227 of LNAI, pages 313–327. Springer, 1997.
J. A. Robinson Automatic deduction with hyper-resolution. Int. J. Computational Mathematics, 1: 227–234, 1965.
L. Shastri and V. Ajjanagadde. From associations to systematic reasoning: A connectionist representation of rules, variables and dynamic bindings using temporal synchrony. Behavioural and Brain Sciences, 16(3): 417–494, September 1993.
J. Slaney. Scott: A model-guided theorem prover. In Proceedings of the International Joint Conference on Artificial Intelligence, pages 109–114, 1993.
D. Turi. Extending s-models to logic programs with negation. In Proceedings of the International Logic Programming Symposium, pages 397–411. MIT Press, 1991.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1998 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bornscheuer, SE. (1998). Integrating reactive and reflective reasoning by generating rational models. In: Antoniou, G., Slaney, J. (eds) Advanced Topics in Artificial Intelligence. AI 1998. Lecture Notes in Computer Science, vol 1502. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0095043
Download citation
DOI: https://doi.org/10.1007/BFb0095043
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-65138-3
Online ISBN: 978-3-540-49561-1
eBook Packages: Springer Book Archive