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UID:141@isdm.umontpellier.fr
DTSTART;TZID=Europe/Paris:20250324T100000
DTEND;TZID=Europe/Paris:20250324T100000
DTSTAMP:20260602T130233Z
URL:https://isdm.umontpellier.fr/events/datalog-fact-explanation-using-gro
 up-sat-solver-3/
SUMMARY:Datalog Fact Explanation Using Group-SAT Solver
DESCRIPTION:Salle des conseils P Raynaud\, au 2ème étage\, du bâtiment 1
 1 dit le château\, 2 Place Pierre Viala Campus La Gaillarde\nSEmantic web
  SeminAr MontpEllier\nPierre BISQUERT (INRAE IATE)\n\nOne of the major ben
 efits of symbolic AI is explainability. When new knowledge is obtained via
  a reasoning process\, it is possible to determine precisely the elements 
 of the knowledge base that yield this knowledge. Typically\, one would use
  a SAT solver to compute the explanations. However\, SAT-solving is comput
 ationally expensive\, and as the knowledge base grows\, the time required 
 increases exponentially.\n\nLabéliséHallesIA
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