Zobrazeno 1 - 10
of 211
pro vyhledávání: '"Schiex T."'
Publikováno v:
Journal Of Artificial Intelligence Research, Volume 29, pages 421-489, 2007
Numerous formalisms and dedicated algorithms have been designed in the last decades to model and solve decision making problems. Some formalisms, such as constraint networks, can express "simple" decision problems, while others are designed to take i
Externí odkaz:
http://arxiv.org/abs/1110.2741
Akademický článek
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Publikováno v:
In Artificial Intelligence 2010 174(7):449-478
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
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Autor:
Mark Guiltinan, Cristian Chaparro, Florent Murat, John Carlson, Valentin Guignon, Mathias Tahi, Emmanuel Guiderdoni, Thierry Legavre, Olivier Fouet, Erika Sallet, Xavier Sabau, Joseph Moroh Akaza, Francis Quetier, Julie Poulain, Schiex T., Michael Axtell, Bertrand Pitollat, Olivier Panaud, Siela Maximova, Manuel Ruiz, Anne Dievart, Zhaorong Ma, Karina Gramacho, Patrick Wincker, Yolande Roguet, Melissa Kramer, Yufan Zhang, Angélique D’Hont, Stephanie Sidibe-Bocs, Claire Lanaud, Xavier Argout, Maguy Rodier-Goud, Laura Gelley, Spencer Brown, Dominique Brunel, Diogenes Infante, Jerome Salse, Jose Fernandes Barbosa-Neto, Zi Sh, Mickael Bourge, Wolfgang Golser, Ismael Kebe, Jean Marc Aury, Francois Sabot, Aurélie Bérard, Christopher Viot, Xiang Song, Pierre Costet, Gaetan Droc, Dave Kudrna, Jetty Siva Ammiraju, Michel Boccara, Didier Clement, Rod Wing, Jerome Gouzy, Michael Abrouk, Stephan Schuster, Ange Marie Risterucci, Ronan Rivalan, W. Richard McCombie, Mathilde Allegre
Publikováno v:
Nature Precedings.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::de636389d328576bfd723e202a1b9259
https://doi.org/10.1038/npre.2010.4908
https://doi.org/10.1038/npre.2010.4908
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
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Publikováno v:
Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence. 2008; Twenty-third AAAI Conference on Artificial Intelligence, Chicago, USA, 2008-07-13-2008-07-17, 253-258
Twenty-third AAAI Conference on Artificial Intelligence
Twenty-third AAAI Conference on Artificial Intelligence, Jul 2008, Chicago, United States. pp.6
Scopus-Elsevier
Twenty-third AAAI Conference on Artificial Intelligence
Twenty-third AAAI Conference on Artificial Intelligence, Jul 2008, Chicago, United States. pp.6
Scopus-Elsevier
International audience; Optimizing a combination of local cost functions on discrete variables is a central problem in many formalisms such as in probabilistic networks, maximum satisfiability, weighted CSP or factor graphs. Recent results have shown
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::a5a5ced0fa466eaf5300f7b4015cc4a2
http://prodinra.inra.fr/record/186572
http://prodinra.inra.fr/record/186572
Publikováno v:
20th International Joint Conference on Artificial Intelligence-IJCAI 2007
20th International Joint Conference on Artificial Intelligence-IJCAI 2007, Jan 2007, Hyderabad, India. pp.6
Web of Science
IJCAI 2007, Proceedings of the 20th International Joint Conference on Artificial Intelligence, Hyderabad, India, January 6-12, 2007. 2007; 20th International Joint Conference on Artificial Intelligence-IJCAI 2007, Hyderabad, IND, 2007-01-06-2007-01-12, 68-73
Scopus-Elsevier
20th International Joint Conference on Artificial Intelligence-IJCAI 2007, Jan 2007, Hyderabad, India. pp.6
Web of Science
IJCAI 2007, Proceedings of the 20th International Joint Conference on Artificial Intelligence, Hyderabad, India, January 6-12, 2007. 2007; 20th International Joint Conference on Artificial Intelligence-IJCAI 2007, Hyderabad, IND, 2007-01-06-2007-01-12, 68-73
Scopus-Elsevier
The Valued (VCSP) framework is a generic optimization framework with a wide range of applications. Soft arc consistency operations transform a VCSP into an equivalent problem by shifting weights between cost functions. The principal aim is to produce
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::8a34ac59e64e3a7ce108dcc8c9dbb10c
https://hal.inrae.fr/hal-02754114
https://hal.inrae.fr/hal-02754114