Dynamic decision making (DM) maps knowledge into DM strategy, which ensures reaching DM aims under given constraints. Under general conditions, Bayesian DM, minimizing expected loss over admissible strategies, has to be used. Existing limitations of the paradigm impede its applicability to complex DM as:
The research aims to overcome these problems. It relies on distributed DM and fully probabilistic design (FPD) of strategies. The goal is to build a firm theoretical background of FPD of distributed DM strategies. Besides, it will enrich available results and unify them into internally consistent theory suitable for a flat cooperation structure.
This aim implies the main tasks: