Abstract
A symbolic assignment problem has been solved by making use of the fact that it can be represented as a decomposable production system. We explain how the structure of the given constraint satisfaction problem (CSP) can be exploited to design a two component architecture of a neural net interacting with a scheduler. We describe the relation of problem parameters to the net design, using a feedforward net with error backpropagation. Different versions of the net design are contrasted. We discuss the advantages of our architecture and relate the results of the connectionist approach to a solving of the problem with backtrack search. The CSP was part of a case study, a knowledge-based system for the automatic configuration of telephone exchanges. An enlargement of the architecture and its application is foreseen.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Abu-Mustafa, Y.S., Neural Networks for Computing?, AIP Conf Proc. 151, 1986, 1–6.
Barnden, John A., Neural-Net Implementation of Complex Symbol-Processing in a Mental Model Approach to Syllogistic Reasoning, Proceedings of IJCAI-89, Detroit, Mich., 1989, 568–573.
Ekeberg, O., and A. Lansner, Automatic Generation of Internal Representations in a Probabilistic Artificial Neural Network, in: Neural Networks from Models to Applications ( Personnaz, L., and G. Dreyfus, eds.), Paris: IDSET, 1989, 179–186.
Haralick, R.M., and G.L. Elliott, Increasing Tree Search Efficiency for Constraint Satisfaction Problems, Artificial Intelligence 14 (3), 1980, 61–76.
Kaindl, H., and H.G. Ziegeler, Some Aspects of Knowledge-Based Configuration, Proceedings AVIGNON ‘80: Expert systems & their applications, Specialized Conference: Artificial Intelligence, Telecommunications & Computer Systems, 1990, 41–54.
Lapedes, A. and R. Farber, Programming a Massively Parallel, Computation Universal System: Static Behaviour, AIP Conf. Proc. 151, 1986, 283–298.
Mackworth, A.K., Constraint Satisfaction, in Encyclopedia of Artificial Intelligence ( Shapiro, S.C., ed.), New York, N.Y.: Wiley, 1987, 205–211.
Nilsson, N.J., Principles of Artificial Intelligence, Tioga Publ. Co., 1980.
Quinlan, J.R., Learning efficient classification procedures and their application to chess end games: in: Machine Learning 2 (Michalski, R.S., J.G. Carbonell, and T.M. Mitchell, eds.), Palo Alto, Ca.: Tioga, 1984, 463–482.
Rumelhart, D., J. McClelland et al. (ed.), Parallel Distributed Processing: Explorations in the Microstructure of Cognition, Cambridge, Ma.: MIT Press, 1986.
Tagliarini, G.A. and E.W. Page, Solving Constraint Satisfaction Problems with Neural Networks, Proc. IEEE First International Conference on Neural Networks, San Diego, 1987.
Ziegeler, H.G., and H. Kaindl, A Cyclic Pattern Resulting from a Constraint Satisfaction Search, working paper, to be presented at the AAAI-90 Workshop on Constraint Directed Reasoning, July 1990.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1990 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ziegeler, H.G., Kratky, K.W. (1990). A Connectionist Realization Applying Knowledge-Compilation and Auto-Segmentation in a Symbolic Assignment Problem. In: Dorffner, G. (eds) Konnektionismus in Artificial Intelligence und Kognitionsforschung. Informatik-Fachberichte, vol 252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-76070-9_13
Download citation
DOI: https://doi.org/10.1007/978-3-642-76070-9_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-53131-9
Online ISBN: 978-3-642-76070-9
eBook Packages: Springer Book Archive