Title: Cooperation via sharing of probabilistic information

Authors: Miroslav Karny, Tatiana V. Guy, Antonella Bodini, Fabrizio Ruggeri

Addresses: Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic, P.O. Box 18, 182 08 Prague, Czech Republic. ' Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic, P.O. Box 18, 182 08 Prague, Czech Republic. ' Institute of Applied Mathematics and Information Technology, National Research Council, via E. Bassini 15, I-20133 Milan, Italy. ' Institute of Applied Mathematics and Information Technology, National Research Council, via E. Bassini 15, I-20133 Milan, Italy

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.

Keywords: Bayesian decision making; multiple participant decision making; information sharing; probabilistic information; cooperation.

DOI: 10.1504/IJCISTUDIES.2009.031344

International Journal of Computational Intelligence Studies, 2009 Vol.1 No.2, pp.139 - 162

Published online: 01 Feb 2010 *

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