Publication details
Programming Constraint Inference Engines
Christian Schulte
Proceedings of the Third International Conference on Principles and Practice of Constraint Programming, Vol. 1330 of Lecture Notes in Computer Science, pp. 519--533, Springer-Verlag, October 1997
Existing constraint programming systems offer a fixed set of inference engines implementing search strategies such as single, all, and best
solution search. This is unfortunate, since new engines cannot be
integrated by the user. The paper presents first-class computation
spaces as abstractions with which the user can program inference engines
at a high level. Using computation spaces, the paper covers several
inference engines ranging from standard search strategies to techniques
new to constraint programming, including limited discrepancy search,
visual search, and saturation. Saturation is an inference method for
tautology-checking used in industrial practice. Computation spaces have
shown their practicability in the constraint programming system Oz.
Download PDF
Show BibTeX
@INPROCEEDINGS{Engines:97,
title = {Programming Constraint Inference Engines},
author = {Christian Schulte},
year = {1997},
month = {oct},
editor = {{Gert Smolka}},
publisher = {{Springer-Verlag}},
booktitle = {Proceedings of the Third International Conference on Principles and Practice of Constraint Programming},
series = {{Lecture Notes in Computer Science}},
volume = {{1330}},
pages = {{519--533}},
address = {{Schloss Hagenberg, Linz, Austria}},
}
Login to edit
Legal notice, Privacy policy