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Modelling Diversity...
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Ingmar, LinneaKTH,Programvaruteknik och datorsystem, SCS
(författare)
Modelling Diversity of Solutions
- Artikel/kapitelEngelska2020
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ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE,2020
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Nummerbeteckningar
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LIBRIS-ID:oai:DiVA.org:kth-299722
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https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-299722URI
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Språk:engelska
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Sammanfattning på:engelska
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Ämneskategori:ref swepub-contenttype
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Ämneskategori:kon swepub-publicationtype
Anmärkningar
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QC 20210816
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For many combinatorial problems, finding a single solution is not enough. This is clearly the case for multi-objective optimization problems, as they have no single "best solution" and, thus, it is useful to find a representation of the non-dominated solutions (the Pareto frontier). However, it also applies to single objective optimization problems, where one may be interested in finding several (close to) optimal solutions that illustrate some form of diversity. The same applies to satisfaction problems. This is because models usually idealize the problem in some way, and a diverse pool of solutions may provide a better choice with respect to considerations that are omitted or simplified in the model. This paper describes a general framework for finding k diverse solutions to a combinatorial problem (be it satisfaction, single-objective or multi-objective), various approaches to solve problems in the framework, their implementations, and an experimental evaluation of their practicality.
Ämnesord och genrebeteckningar
Biuppslag (personer, institutioner, konferenser, titlar ...)
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de la Banda, Maria GarciaMonash Univ, Melbourne, Vic, Australia.
(författare)
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Stuckey, Peter J.Monash Univ, Melbourne, Vic, Australia.
(författare)
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Tack, GuidoMonash Univ, Melbourne, Vic, Australia.
(författare)
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KTHProgramvaruteknik och datorsystem, SCS
(creator_code:org_t)
Sammanhörande titlar
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Ingår i:Thirty-fourth AAAI Conference on Artificial Intelligence, the thirty-second innovative applications of artificial intelligence conference and the tenth AAAI symposium on educational advances in artificial intelligence: ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE, s. 1528-1535
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