Solving Temporal CSPs via Enumeration and SAT Compilation

The constraint satisfaction problem (CSP) is a powerful framework used in theoretical computer science for formulating a  multitude of problems. The CSP over a constraint language Γ (CSP(Γ)) is the decision problem of verifying whether a set of constraints based on the relations in Γ admits a satisf...

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Main Author: Eriksson, Leif
Format: Others
Language:English
Published: Linköpings universitet, Institutionen för datavetenskap 2019
Subjects:
CSP
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-162482
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spelling ndltd-UPSALLA1-oai-DiVA.org-liu-1624822019-12-11T15:42:34ZSolving Temporal CSPs via Enumeration and SAT CompilationengEriksson, LeifLinköpings universitet, Institutionen för datavetenskap2019CSPAlgorithmsComputer SciencesDatavetenskap (datalogi)The constraint satisfaction problem (CSP) is a powerful framework used in theoretical computer science for formulating a  multitude of problems. The CSP over a constraint language Γ (CSP(Γ)) is the decision problem of verifying whether a set of constraints based on the relations in Γ admits a satisfying assignment or not. Temporal CSPs are a special subclass of CSPs frequently encountered in AI. Here, the relations are first-order definable in the structure (Q;<), i.e the rationals with the usual order. These problems have previously often been solved by either enumeration or SAT compilation. We study a restriction of temporal CSPs where the constraint language is limited to logical disjunctions of <-, =-, ≠- and ≤-relations, and were each constraint contains at most k such basic relations (CSP({<,=,≠,≤}∨k)).   Every temporal CSP with a finite constraint language Γ is polynomial-time reducible to CSP({<,=,≠,≤}∨k) where k is only dependent on Γ. As this reduction does not increase the number of variables, the time complexity of CSP(Γ) is never worse than that of CSP({<,=,≠,≤}∨k). This makes the complexity of CSP({<,=,≠,≤}∨k) interesting to study.   We develop algorithms combining enumeration and SAT compilation to solve CSP({<,=,≠,≤}∨k), and study the asymptotic behaviour of these algorithms for different classes. Our results show that all finite constraint languages Γ first order definable over (Q;<) are solvable in O*(((1/(eln(2))-ϵk)n)^n) time for some ϵk>0 dependent on Γ. This is strictly better than O*((n/(eln(2)))^n), i.e. O*((0.5307n)^n), achieved by enumeration algorithms. Some examples of upper bounds on time complexity achieved in the thesis are CSP({<}∨2) in O*((0.1839n)^n) time, CSP({<,=,≤}∨2) in O*((0.2654n)^n) time, CSP({<,=,≠}∨3) in O*((0.4725n)^n) time and CSP({<,=,≠,≤}∨3) in O*((0.5067n)^n) time. For CSP({<}∨2) this should be compared to the bound O*((0.3679n)^n), from previously known enumeration algorithms.       Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-162482application/pdfinfo:eu-repo/semantics/openAccess
collection NDLTD
language English
format Others
sources NDLTD
topic CSP
Algorithms
Computer Sciences
Datavetenskap (datalogi)
spellingShingle CSP
Algorithms
Computer Sciences
Datavetenskap (datalogi)
Eriksson, Leif
Solving Temporal CSPs via Enumeration and SAT Compilation
description The constraint satisfaction problem (CSP) is a powerful framework used in theoretical computer science for formulating a  multitude of problems. The CSP over a constraint language Γ (CSP(Γ)) is the decision problem of verifying whether a set of constraints based on the relations in Γ admits a satisfying assignment or not. Temporal CSPs are a special subclass of CSPs frequently encountered in AI. Here, the relations are first-order definable in the structure (Q;<), i.e the rationals with the usual order. These problems have previously often been solved by either enumeration or SAT compilation. We study a restriction of temporal CSPs where the constraint language is limited to logical disjunctions of <-, =-, ≠- and ≤-relations, and were each constraint contains at most k such basic relations (CSP({<,=,≠,≤}∨k)).   Every temporal CSP with a finite constraint language Γ is polynomial-time reducible to CSP({<,=,≠,≤}∨k) where k is only dependent on Γ. As this reduction does not increase the number of variables, the time complexity of CSP(Γ) is never worse than that of CSP({<,=,≠,≤}∨k). This makes the complexity of CSP({<,=,≠,≤}∨k) interesting to study.   We develop algorithms combining enumeration and SAT compilation to solve CSP({<,=,≠,≤}∨k), and study the asymptotic behaviour of these algorithms for different classes. Our results show that all finite constraint languages Γ first order definable over (Q;<) are solvable in O*(((1/(eln(2))-ϵk)n)^n) time for some ϵk>0 dependent on Γ. This is strictly better than O*((n/(eln(2)))^n), i.e. O*((0.5307n)^n), achieved by enumeration algorithms. Some examples of upper bounds on time complexity achieved in the thesis are CSP({<}∨2) in O*((0.1839n)^n) time, CSP({<,=,≤}∨2) in O*((0.2654n)^n) time, CSP({<,=,≠}∨3) in O*((0.4725n)^n) time and CSP({<,=,≠,≤}∨3) in O*((0.5067n)^n) time. For CSP({<}∨2) this should be compared to the bound O*((0.3679n)^n), from previously known enumeration algorithms.      
author Eriksson, Leif
author_facet Eriksson, Leif
author_sort Eriksson, Leif
title Solving Temporal CSPs via Enumeration and SAT Compilation
title_short Solving Temporal CSPs via Enumeration and SAT Compilation
title_full Solving Temporal CSPs via Enumeration and SAT Compilation
title_fullStr Solving Temporal CSPs via Enumeration and SAT Compilation
title_full_unstemmed Solving Temporal CSPs via Enumeration and SAT Compilation
title_sort solving temporal csps via enumeration and sat compilation
publisher Linköpings universitet, Institutionen för datavetenskap
publishDate 2019
url http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-162482
work_keys_str_mv AT erikssonleif solvingtemporalcspsviaenumerationandsatcompilation
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