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Galois connections for patterns: an algebra of labelled graphs

Abstract:
A pattern is a generic instance of a binary constraint satisfaction problem (CSP) in which the compatibility of certain pairs of variable-value assignments may be unspecified. The notion of forbidden pattern has led to the discovery of several novel tractable classes for the CSP. However, for this field to come of age it is time for a theoretical study of the algebra of patterns. We present a Galois connection between lattices composed of sets of forbidden patterns and sets of generic instances, and investigate its consequences. We then extend patterns to augmented patterns and exhibit a similar Galois connection. Augmented patterns are a more powerful language than flat (i.e. non-augmented) patterns, as we demonstrate by showing that, for any k≥ 1, instances with tree-width bounded by k cannot be specified by forbidding a finite set of flat patterns but can be specified by a finite set of augmented patterns. A single finite set of augmented patterns can also describe the class of instances such that each instance has a weak near-unanimity polymorphism of arity k (thus covering all tractable language classes).We investigate the power of forbidding augmented patterns and discuss their potential for describing new tractable classes.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/978-3-030-72308-8_9

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Institution:
University of Oxford
Department:
COMPUTER SCIENCE
Sub department:
Computer Science
Role:
Author
ORCID:
0000-0003-4333-8506
More by this author
Institution:
University of Oxford
Role:
Author

Contributors

Role:
Editor
Role:
Editor
Role:
Editor
Role:
Editor


Publisher:
Springer
Host title:
Proceedings of the International Workshop on Graph Structures for Knowledge Representation and Reasoning
Volume:
12640
Issue:
2020
Pages:
125-150
Series:
Lecture Notes in Computer Science
Publication date:
2021-03-16
Acceptance date:
2021-01-15
Event title:
International Workshop on Graph Structures for Knowledge Representation and Reasoning (GKR 2020)
Event location:
Online
Event website:
https://graphkr.github.io/
Event start date:
2020-09-05
Event end date:
2020-09-05
DOI:
EISSN:
1611-3349
ISSN:
0302-9743
ISBN:
9783030723071


Language:
English
Keywords:
Pubs id:
1171073
Local pid:
pubs:1171073
Deposit date:
2021-04-26

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