Please use this identifier to cite or link to this item:
doi:10.22028/D291-25045
Title: | Propagation techniques in WAM-based architectures : the FIDO-III approach |
Author(s): | Hein, Hans-Günther |
Language: | English |
Year of Publication: | 1993 |
OPUS Source: | Kaiserslautern ; Saarbrücken : DFKI, 1993 |
SWD key words: | Künstliche Intelligenz |
DDC notations: | 004 Computer science, internet |
Publikation type: | Report |
Abstract: | In this paper we develop techniques to implement finite domain constraints into the Warren Abstract Machine (WAM) to solve large combinatorial problems effciently. The WAM is the de facto standard model for compiling PROLOG. The FIDO system ("FInite Domain';) provides the same functionality as the finite domain part of CHIP. The extension includes the integration of several new variable types (suspended variables, domain variables and suspended domain variables) into the WAM. The "firing conditions'; are lookahead and forward control schemes known from CHIP. We have developed a constraint model where the constraint is divided into constraint initialization code, constraint testing code and constraint body. Furthermore, we supply a deeply integrated WAM builtin to realize the first fail principle. Besides the summary of the important theoretical results, the specification of the compilation process in the WAM Compilation Scheme is given. We also present a simple graphical analysis method to estimate the computational burden of lookahead and forward constraints. The work is an instance of exploring finite domain consistency techniques in logic programming belonging to the FIDO lab within the ARC-TEC project. |
Link to this record: | urn:nbn:de:bsz:291-scidok-38890 hdl:20.500.11880/25101 http://dx.doi.org/10.22028/D291-25045 |
Series name: | Technical memo / Deutsches Forschungszentrum für Künstliche Intelligenz [ISSN 0946-0071] |
Series volume: | 93-04 |
Date of registration: | 7-Jul-2011 |
Faculty: | SE - Sonstige Einrichtungen |
Department: | SE - DFKI Deutsches Forschungszentrum für Künstliche Intelligenz |
Collections: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
Files for this record:
File | Description | Size | Format | |
---|---|---|---|---|
TM_93_04.pdf | 1,28 MB | Adobe PDF | View/Open |
Items in SciDok are protected by copyright, with all rights reserved, unless otherwise indicated.