Institute of Information Theory and Automation

Fully probabilistic design of dynamic decision strategies

Project leader: Ing. Miroslav Kárný, DrSc.
Department: AS
Supported by (ID): GA102/08/0567
Grantor: Czech Science Foundation
Type of project: theoretical
Duration: 2008 - 2011
More info: here
Publications at UTIA: list


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: 1) Complexity of the information processing often crosses resources accessible. 2) Quantification of domain-specific knowledge, aims and constraints is weakly supported. It concerns mapping of domain-specific elements on probabilistic distributions (pd). 3) Methodology of the DM with multiple aims is incomplete. The project aims to overcome these problems. It relies on, distributed DM and fully probabilistic design (FPD) of strategies. The project aims at building 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.

Project team:
Responsible for information: AS
Last modification: 14.11.2017
Institute of Information Theory and Automation