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UID:/NewsandEvents/Archives/2023/newsitem/14124/24
 -February-2023-Formalisation-Optimisation-Algorith
 ms-Mechanisms-FOAM-Gregor-Behnke
DTSTAMP:20230303T020642
SUMMARY:Formalisation, Optimisation, Algorithms, M
 echanisms (FOAM), Gregor Behnke
ATTENDEE;ROLE=Speaker:Gregor Behnke
DTSTART;TZID=Europe/Amsterdam:20230224T150000
DTEND;TZID=Europe/Amsterdam:20230224T161500
LOCATION:Room L3.36, ILLC Lab42, Science Park 900,
  Amsterdam / online (Zoom)
DESCRIPTION:Abstract:  Planning models are usually
  defined in lifted, i.e., first order formalisms, 
 while most solvers need (variable-free) grounded r
 epresentations. Though techniques for grounding pr
 une unnecessary parts of the model, grounding migh
 t – nevertheless – be prohibitively expensive in t
 erms of runtime. To overcome this issue, there has
  been renewed interest in solving planning problem
 s based on the lifted representation in the last y
 ears.  While these approaches are based on (heuris
 tic) search, we present an encoding of lifted clas
 sical planning in propositional logic and use SAT 
 solvers to solve it. Evaluating this approach show
 s that it is competitive with the heuristic search
 -based approaches in satisficing planning and even
  outperforms them if we are looking for (length-)o
 ptimal solutions.
X-ALT-DESC;FMTTYPE=text/html:\n  <p>Abstract:<br>\
 n  Planning models are usually defined in lifted, 
 i.e., first order formalisms, while most solvers n
 eed (variable-free) grounded representations. Thou
 gh techniques for grounding prune unnecessary part
 s of the model, grounding might – nevertheless – b
 e prohibitively expensive in terms of runtime. To 
 overcome this issue, there has been renewed intere
 st in solving planning problems based on the lifte
 d representation in the last years.</p>\n  <p>Whil
 e these approaches are based on (heuristic) search
 , we present an encoding of lifted classical plann
 ing in propositional logic and use SAT solvers to 
 solve it. Evaluating this approach shows that it i
 s competitive with the heuristic search-based appr
 oaches in satisficing planning and even outperform
 s them if we are looking for (length-)optimal solu
 tions.</p>\n
URL:https://events.illc.uva.nl/FOAM/posts/talk1/
CONTACT:Gregor Behnke at g.behnke at uva.nl
CONTACT:Ronald de Haan at r.dehaan at uva.nl
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