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        <identifier>oai:drops-oai.dagstuhl.de:11843</identifier>
        <datestamp>2024-03-06T10:27:11Z</datestamp>
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          <dc:title>Deduction Beyond Satisfiability (Dagstuhl Seminar 19371)</dc:title>
          <dc:creator>Fuhs, Carsten</dc:creator>
          <dc:creator>Rümmer, Philipp</dc:creator>
          <dc:creator>Schmidt, Renate</dc:creator>
          <dc:creator>Tinelli, Cesare</dc:creator>
          <dc:subject>abduction</dc:subject>
          <dc:subject>automated deduction</dc:subject>
          <dc:subject>interpolation</dc:subject>
          <dc:subject>quantifier elimination</dc:subject>
          <dc:subject>synthesis</dc:subject>
          <dc:description>Research in automated deduction is traditionally focused on &#13;
the problem of determining the satisfiability of formulas &#13;
or, more generally, on solving logical problems with yes/no answers.&#13;
Thanks to recent advances that have dramatically increased the power&#13;
of automated deduction tools, there is now a growing interest&#13;
in extending deduction techniques to attack logical problems &#13;
with more complex answers.&#13;
These include both problems with a long history,&#13;
such as quantifier elimination,&#13;
which are now being revisited in light of the new methods,&#13;
as well as newer problems such as&#13;
minimal unsatisfiable cores computation, &#13;
model counting&#13;
for propositional or first-order formulas,&#13;
Boolean or SMT constraint optimization, &#13;
generation of interpolants,&#13;
abductive reasoning, and&#13;
syntax-guided synthesis.&#13;
Such problems arise in a variety of applications including&#13;
the analysis of probabilistic systems&#13;
(where properties like safety or liveness can be established&#13;
only probabilistically),&#13;
network verification (with relies on model counting),&#13;
the computation of tight complexity bounds for programs,&#13;
program synthesis, model checking (where interpolation or&#13;
abductive reasoning can be used to achieve scale), and&#13;
ontology-based information processing.&#13;
The seminar brought together researchers and practitioners from many of the often disjoint sub-communities &#13;
interested in the problems above.&#13;
The unifying theme of the seminar was how to harness and extend&#13;
the power of automated deduction methods to solve problems&#13;
with more complex answers than binary ones.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Carsten Fuhs and Philipp Rümmer and Renate Schmidt and Cesare Tinelli</dc:contributor>
          <dc:date>2020</dc:date>
          <dc:relation>Is Part Of Dagstuhl Reports, Volume 9, Issue 9 (2020)</dc:relation>
          <dc:type>Article</dc:type>
          <dc:type>Text</dc:type>
          <dc:type>doc-type:ResearchArticle</dc:type>
          <dc:type>publishedVersion</dc:type>
          <dc:format>application/pdf</dc:format>
          <dc:identifier>doi:10.4230/DagRep.9.9.23</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-118432</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/DagRep.9.9.23</dc:identifier>
          <dc:language>eng</dc:language>
          <dc:rights>https://creativecommons.org/licenses/by/3.0/legalcode</dc:rights>
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