Cooperation via sharing of probabilistic information Online publication date: Mon, 01-Feb-2010
by Miroslav Karny, Tatiana V. Guy, Antonella Bodini, Fabrizio Ruggeri
International Journal of Computational Intelligence Studies (IJCISTUDIES), Vol. 1, No. 2, 2009
Abstract: The paper concerns a cooperation problem in multiple participant decision making (DM). A fully scalable cooperation model with individual participants being Bayesian decision makers who use fully probabilistic design of the optimal decision strategy is presented. The solution suggests a flat structure of cooperation, where each participant interacts with several 'neighbours'. The cooperation consists in providing probabilistic distributions a participant uses for its DM. The group DM is then determined by a way of exploitation of the offered non-standard (probabilistic) fragmental information. The paper proposes a systematic procedure by formulating and solving the exploitation problem in a Bayesian way.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Intelligence Studies (IJCISTUDIES):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com