M.A. Reuter; U.M.J. Boin; A van Schaik; E. Verhoef; K. Heiskanen; Yongxiang Yang; G. Georgalli Elsevier Science (2005) Saatavuus: Loppuunmyyty Kovakantinen kirja
M.A. Reuter; U.M.J. Boin; van Schaik, A,; K. Heiskanen; E. Verhoef; Yongxiang Yang; G. Georgalli Elsevier Science (2005) Saatavuus: Painos loppu CD-levy
Yang Xiang; Alfredo Cuzzocrea; Michael Hobbs; Wanlei Zhou Springer-Verlag Berlin and Heidelberg GmbH & Co. KG (2011) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Yang Xiang (ed.); Ivan Stojmenovic (ed.); Bernady O. Apduhan (ed.); Guojun Wang (ed.); Koji Nakano (ed.); Albert Y. Zomaya Springer (2012) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Yang Xiang; Ivan Stojmenovic; Bernady O. Apduhan; Guojun Wang; Koji Nakano; Albert Y. Zomaya Springer-Verlag Berlin and Heidelberg GmbH & Co. KG (2012) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Yang Xiang; Mukaddim Pathan; Xiaohui Tao; Hua Wang Springer-Verlag Berlin and Heidelberg GmbH & Co. KG (2012) Saatavuus: Tilaustuote Pehmeäkantinen kirja
This 2002 book investigates the opportunities in building intelligent decision support systems offered by multi-agent distributed probabilistic reasoning. Probabilistic reasoning with graphical models, also known as Bayesian networks or belief networks, has become increasingly an active field of research and practice in artificial intelligence, operations research and statistics. The success of this technique in modeling intelligent decision support systems under the centralized and single-agent paradigm has been striking. Yang Xiang extends graphical dependence models to the distributed and multi-agent paradigm. He identifies the major technical challenges involved in such an endeavor and presents the results. The framework developed in the book allows distributed representation of uncertain knowledge on a large and complex environment embedded in multiple cooperative agents, and effective, exact and distributed probabilistic inference.
