Konferenční příspěvek

Abstracts of Contributions to 4th International Workshop on Data-Algorithms-Decision Making

ÚTIA AV ČR, v.v.i

Praha

2008

Ing. Miroslav Kárný, DrSc. (ÚTIA - Oddělení adaptivních systémů)

Bayesian theory, multiparticipant, dynamic decision making,

Inherent complexity of dynamic decision making (DM) under uncertainty, that precludes implementation of formally optimal strategies, has been primary motivation for the reported research. Distributed DM seems to be only way out of this "curse of dimensionality". A systematic and fully scalable solution has to cope with a flatly organized structures. Otherwise, central decision makers and communication channels to them are either overloaded or information loss is too high. The proposed methodology is of an independent interest since it can be used for model and aim elicitation.