Název:
On Approximate Fully Probabilistic Design of Decision-Making Units
Autoři:
Kárný, Miroslav Typ dokumentu: Příspěvky z konference Konference/Akce: The 3rd International Workshop on Scalable Decision Making: Uncertainty, Imperfection, Deliberation held in conjunction with ECML/PKDD 2013, Prague (CZ), 2013-09-23 / 2013-09-23
Rok:
2013
Jazyk:
eng
Abstrakt: An efficient support of a single decision maker is vital in constructing scalable systems addressing complex decision-making (DM) tasks. Fully probabilistic design (FPD) of DM strategies, an extension of dynamic Bayesian DM, provides a firm basis for such a support. The limited cognitive and evaluation resources of the supported decision maker cause that theoretically optimal solutions are realised only approximately. Thus, the truly efficient support has to include reliable means for constructing approximate solutions of DM subtasks. The current paper deals with the design of the approximately optimal DM strategy for a known environment model and adequately described DM preferences. The design relies on: a) the explicit minimiser found within FPD; b) randomised nature of the strategy provided by FPD.
Klíčová slova:
Bayesian learning; decision making; fully probabilistic design of DM strategies; linear-quadratic DM; minimum cross-entropy principle Číslo projektu: GA13-13502S (CEP) Poskytovatel projektu: GA ČR Zdrojový dokument: Preprints of the 3rd International Workshop on Scalable Decision Making held in conjunction with ECML/PKDD 2013, ISBN 978-80-903834-8-7