0367271 20240103195840.320111125235959.9 000298460300007 81355127223 10.1016/j.ins.2011.09.018 9 s. cav_un_epca*02567520020-02551861 (2012)105-113Elsevier Bayesian decision making Fully probabilistic design Kullback–Leibler divergence Unified decision making cav_un_auth*0101124 Kárný Miroslav Adaptivní systémy Department of Adaptive Systems AS AS UTIA-B Department of Adaptive Systems Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101141 Kroupa Tomáš Matematická teorie rozhodování Department of Decision Making Theory MTR MTR UTIA-B Department of Decision Making Theory Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2011/AS/karny-0367271.pdf 2C06001 GA MŠk CZ cav_un_auth*0217685 GA102/08/0567 GA ČR cav_un_auth*0239566 CEZ:AV0Z10750506 This text provides background of fully probabilistic design (FPD) of decision-making strategies and shows that it is a proper extension of the standard Bayesian decision making. FPD essentially minimises Kullback–Leibler divergence of closed-loop model on its ideal counterpart. The inspection of the background is important as the current motivation for FPD is mostly heuristic one, while the technical development of FPD confirms its far reaching possibilities. FPD unifies and simplifies subtasks and elements of decision making under uncertainty. For instance, (i) both system model and decision preferences are expressed in common probabilistic language; (ii) optimisation is simplified due to existence of explicit minimiser in stochastic dynamic programming; (iii) DM methodology for single and multiple aims is unified. 2012 BB 2 4 A 4a 20231122134749.9 http://hdl.handle.net/11104/0202012 COMPUTERSCIENCEINFORMATIONSYSTEMS 3.676 0.762 4.7 0.02864 0.945 10013 425 79 2.127 36.86 4.8 Q1 77.575 95.833 Q1 Q1 2012 Soubory v repozitáři: karny-0367271.pdf 81355127223 SCOPUS 000298460300007 WOS cav_un_epca*0256752 Information Sciences 0020-0255 1872-6291 Roč. 186 č. 1 2012 105 113 Elsevier