<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-23T07:05:19Z</responseDate><request verb="GetRecord" identifier="oai:www.repository.cam.ac.uk:1810/276188" metadataPrefix="uketd_dc">https://api.repository.cam.ac.uk/server/oai/request</request><GetRecord><record><header><identifier>oai:www.repository.cam.ac.uk:1810/276188</identifier><datestamp>2025-12-19T18:09:07Z</datestamp><setSpec>com_1810_219481</setSpec><setSpec>com_1810_256065</setSpec><setSpec>col_1810_219482</setSpec></header><metadata><uketd_dc:uketddc xmlns:uketd_dc="http://naca.central.cranfield.ac.uk/ethos-oai/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:uketdterms="http://naca.central.cranfield.ac.uk/ethos-oai/terms/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://naca.central.cranfield.ac.uk/ethos-oai/2.0/ http://naca.central.cranfield.ac.uk/ethos-oai/2.0/uketd_dc.xsd">
   <dc:title>Descriptive complexity of constraint problems</dc:title>
   <dc:identifier xsi:type="dcterms:DOI">10.17863/CAM.23470</dc:identifier>
   <dc:creator>Wang, Pengming</dc:creator>
   <uketdterms:advisor>Dawar, Anuj</uketdterms:advisor>
   <uketdterms:authoridentifier xsi:type="uketdterms:ORCID">0000000340148248</uketdterms:authoridentifier>
   <dcterms:abstract>Constraint problems are a powerful framework in which many common combinatorial 
problems can be expressed. Examples include graph colouring problems, 
Boolean satisfaction, graph cut problems, systems of equations, and many more. 
One typically distinguishes between constraint satisfaction problems (CSPs),
which model strictly decision problems, and so-called valued constraint satisfaction problems
(VCSPs), which also include optimisation
problems.

A key open problem in this field is the long-standing dichotomy conjecture
by Feder and Vardi. It claims that CSPs only fall into two categories:
Those that are NP-complete, and those that are solvable in polynomial time.
This stands in contrast to Ladner's theorem, which, assuming P$\neq$NP, guarantees
the existence of problems that are neither NP-complete, nor in P,
making CSPs an exceptional class of problems. While the Feder-Vardi conjecture
is proven to be true in a number of special cases, it is still open in the
general setting. (Recent claims affirming the conjecture are not considered here, 
as they have not been peer-reviewed yet.)

In this thesis, we approach the complexity of constraint problems from a descriptive
complexity perspective. Namely, instead of studying the computational resources
necessary to solve certain constraint problems, we consider the expressive power
necessary to define these problems in a logic. We obtain several results in this
direction. For instance, we show that Schaefer's dichotomy result for the case of 
CSPs over the Boolean domain
can be framed as a definability result: Either a CSP is definable in fixed-point logic
with rank (FPR), or it is NP-hard. Furthermore, we show that a dichotomy 
exists also in the general case. For VCSPs over arbitrary domains, 
we show that a VCSP is either definable
in fixed-point logic with counting (FPC), or it is not definable in infinitary
logic with counting.

We show that these definability dichotomies also have algorithmic implications.
In particular, using our results on the definability of VCSPs, we prove
a dichotomy on the number of levels in the Lasserre hierarchy necessary to obtain
an exact solution: For a finite-valued VCSP, either it is solved by the first
level of the hierarchy, or one needs $\Omega(n)$ levels.

Finally, we explore how other methods from finite model theory can be useful
in the context of constraint problems. We consider pebble games for finite variable 
logics in this context, and expose new connections between CSPs, pebble games, 
and homomorphism preservation results.</dcterms:abstract>
   <uketdterms:institution>University of Cambridge</uketdterms:institution>
   <dcterms:issued>2018-10-13</dcterms:issued>
   <dc:type>Thesis</dc:type>
   <uketdterms:qualificationlevel>Doctoral</uketdterms:qualificationlevel>
   <uketdterms:qualificationname>Doctor of Philosophy (PhD)</uketdterms:qualificationname>
   <dc:language>en</dc:language>
   <dcterms:isReferencedBy xsi:type="dcterms:URI">https://www.repository.cam.ac.uk/handle/1810/276188</dcterms:isReferencedBy>
   <dc:identifier xsi:type="dcterms:URI">https://www.repository.cam.ac.uk/bitstreams/74dfacf4-8208-4d96-a318-54d7471b1aed/download</dc:identifier>
   <uketdterms:checksum xsi:type="uketdterms:MD5">12823e96c3e4bf1f921596ff9f7ee12b</uketdterms:checksum>
   <dcterms:license>https://www.repository.cam.ac.uk/bitstreams/a242f641-cd3b-4da5-8b0f-2987262b8f9f/download</dcterms:license>
   <uketdterms:checksum xsi:type="uketdterms:MD5">87eda9de84448d1f82354d60eee3eb5f</uketdterms:checksum>
   <dc:rights>https://www.rioxx.net/licenses/all-rights-reserved/</dc:rights>
   <dc:subject>Complexity theory</dc:subject>
   <dc:subject>Constraint satisfaction</dc:subject>
   <dc:subject>Logic</dc:subject>
   <dc:subject>Computer science</dc:subject>
   <dc:subject>Optimisation</dc:subject>
</uketd_dc:uketddc>
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