Cooperation via sharing of probabilistic information

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.