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        <datestamp>2024-03-06T10:40:43Z</datestamp>
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          <dc:title>Current Trends and New Perspectives for First-Order Model Checking (Invited Talk)</dc:title>
          <dc:creator>Kreutzer, Stephan</dc:creator>
          <dc:subject>Finite Model Theory</dc:subject>
          <dc:subject>Computational Model Theory</dc:subject>
          <dc:subject>Algorithmic Meta Theorems</dc:subject>
          <dc:subject>Model-Checking</dc:subject>
          <dc:subject>Logical Approaches in Graph Theory</dc:subject>
          <dc:description>The model-checking problem for a logic LLL is the problem &#13;
of decidig for a given formula phi in LLL and structure &#13;
AA whether the formula is true in the structure, i.e. whether &#13;
AA models phi.&#13;
	&#13;
Model-checking for logics such as First-Order Logic (FO) or &#13;
Monadic Second-Order Logic (MSO) has been studied intensively&#13;
in the literature, especially in the context of algorithmic meta-theorems&#13;
within the framework of parameterized complexity. However, in the past the&#13;
focus of this line of research was model-checking on classes of&#13;
sparse graphs, e.g. planar graphs, graph classes excluding a&#13;
minor or classes which are nowhere dense. By now, the complexity of&#13;
first-order model-checking on sparse classes of graphs is completely &#13;
understood. Hence, current research now focusses mainly on classes of &#13;
dense graphs.&#13;
	&#13;
In this talk we will briefly review the known results on sparse classes &#13;
of graphs and explain the complete classification of classes of sparse &#13;
graphs on which first-order model-checking is tractable.&#13;
In the second part we will then focus on recent and ongoing research&#13;
analysing the complexity of first-order model-checking on classes of &#13;
dense graphs.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Stephan Kreutzer</dc:contributor>
          <dc:date>2017</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 82, 26th EACSL Annual Conference on Computer Science Logic (CSL 2017)</dc:relation>
          <dc:type>InProceedings</dc:type>
          <dc:type>Text</dc:type>
          <dc:type>doc-type:ResearchArticle</dc:type>
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          <dc:format>application/pdf</dc:format>
          <dc:identifier>doi:10.4230/LIPIcs.CSL.2017.4</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-77095</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CSL.2017.4</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/3.0/legalcode</dc:rights>
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