1 Ocak 2018 Konferans bildirisi Açık Erişim

Baspinar, Baris; Koyuncu, Emre

Dublin Core

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<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:creator>Baspinar, Baris</dc:creator>
  <dc:creator>Koyuncu, Emre</dc:creator>
  <dc:date>2018-01-01</dc:date>
  <dc:description>The mission-threat analysis is the key factor in air combat missions. The strategic success evaluation of a mission is done through survivability assessment. The mission assessment process begins with the modeling of threats in which a hostile environment can be constructed through these models. Then, based on the environment model including stochasticity, an optimum strategy maximizing the aircraft's survivability is obtained. This study proposes a survivability analysis and optimal mission planning methodology using reinforcement learning for an aircraft flying in a human-made and hostile natural environment.</dc:description>
  <dc:identifier>https://aperta.ulakbim.gov.trrecord/31943</dc:identifier>
  <dc:identifier>oai:zenodo.org:31943</dc:identifier>
  <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
  <dc:rights>http://www.opendefinition.org/licenses/cc-by</dc:rights>
  <dc:title>Survivability based Optimal Air Combat Mission Planning with Reinforcement Learning</dc:title>
  <dc:type>info:eu-repo/semantics/conferencePaper</dc:type>
  <dc:type>publication-conferencepaper</dc:type>
</oai_dc:dc>