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<bibitem type="J">   <ARLID>0508962</ARLID> <utime>20250310141226.2</utime><mtime>20190930235959.9</mtime>   <SCOPUS>85071921926</SCOPUS> <WOS>000494883700007</WOS>  <DOI>10.1016/j.ins.2019.08.082</DOI>           <title language="eng" primary="1">Fully Probabilistic Design Unifies and Supports Dynamic Decision Making Under Uncertainty</title>  <specification> <page_count>15 s.</page_count> <media_type>P</media_type> </specification>    <serial><ARLID>cav_un_epca*0256752</ARLID><ISSN>0020-0255</ISSN><title>Information Sciences</title><part_num/><part_title/><volume_id>509</volume_id><volume>1 (2020)</volume><page_num>104-118</page_num><publisher><place/><name>Elsevier</name><year/></publisher></serial>    <keyword>Dynamic decision making</keyword>   <keyword>Uncertainty</keyword>   <keyword>Cross entropy</keyword>   <keyword>Performance indices</keyword>    <author primary="1"> <ARLID>cav_un_auth*0101124</ARLID> <name1>Kárný</name1> <name2>Miroslav</name2> <institution>UTIA-B</institution> <full_dept language="cz">Adaptivní systémy</full_dept> <full_dept language="eng">Department of Adaptive Systems</full_dept> <department language="cz">AS</department> <department language="eng">AS</department> <full_dept>Department of Adaptive Systems</full_dept> <fullinstit>Ústav teorie informace a automatizace AV ČR, v. v. i.</fullinstit> </author>   <source> <url>http://library.utia.cas.cz/separaty/2019/AS/karny-0508962.pdf</url> </source> <source> <url>https://www.sciencedirect.com/science/article/pii/S0020025519308230</url>  </source>        <cas_special> <project> <project_id>LTC18075</project_id> <agency>GA MŠk</agency> <country>CZ</country> <ARLID>cav_un_auth*0372050</ARLID> </project>  <abstract language="eng" primary="1">The fully probabilistic design (FPD) of decision strategies models the closed decision loop as well as decision aims and constraints by joint probabilities of involved variables. FPD takes the minimiser of cross entropy (CE) of the closed-loop model to its ideal counterpart, expressing the decision aims and constraints, as the optimal strategy. FPD: (a) got an axiomatic basis. (b) extended the decision making (DM) optimising a subjective expected utility (SEU). (c) was nontrivially applied. (d) advocated CE as a proper similarity measure for an approximation of a given probability distribution. (d) generalised the minimum CE principle for a choice of the distribution, which respects its incomplete specification. (e) has opened a way to the cooperation based on sharing of probability distributions. When trying to survey the listed results, scattered in a range of publications, we have found that the results under (b), (d) and (e) can be refined and non-trivially generalised. This determines the paper aims: to provide a complete concise description of FPD with its use and open problems outlined.</abstract>     <result_subspec>WOS</result_subspec> <RIV>BC</RIV> <FORD0>10000</FORD0> <FORD1>10200</FORD1> <FORD2>10201</FORD2>    <reportyear>2021</reportyear>     <unknown tag="mrcbC52"> 4 A sml 4as 2rh 20241106135747.8 2 R hod 20250310141204.9 20250310141226.2 </unknown> <inst_support> RVO:67985556 </inst_support>  <permalink>http://hdl.handle.net/11104/0299775</permalink>   <confidential>S</confidential>  <contract> <name>Rights &amp; Access</name> <date>20190910</date> <note>Copyright agreement</note> </contract> <unknown tag="mrcbC86"> 3+4 Article Computer Science Information Systems </unknown> <unknown tag="mrcbC91"> C </unknown>         <unknown tag="mrcbT16-e">COMPUTERSCIENCE.INFORMATIONSYSTEMS</unknown> <unknown tag="mrcbT16-f">6.524</unknown> <unknown tag="mrcbT16-g">2.857</unknown> <unknown tag="mrcbT16-h">4.9</unknown> <unknown tag="mrcbT16-i">0.04905</unknown> <unknown tag="mrcbT16-j">1.331</unknown> <unknown tag="mrcbT16-k">44038</unknown> <unknown tag="mrcbT16-q">243</unknown> <unknown tag="mrcbT16-s">1.524</unknown> <unknown tag="mrcbT16-y">43.16</unknown> <unknown tag="mrcbT16-x">7.51</unknown> <unknown tag="mrcbT16-3">16801</unknown> <unknown tag="mrcbT16-4">Q1</unknown> <unknown tag="mrcbT16-5">6.026</unknown> <unknown tag="mrcbT16-6">919</unknown> <unknown tag="mrcbT16-7">Q1</unknown> <unknown tag="mrcbT16-B">91.608</unknown> <unknown tag="mrcbT16-C">89.1</unknown> <unknown tag="mrcbT16-D">Q1*</unknown> <unknown tag="mrcbT16-E">Q1</unknown> <unknown tag="mrcbT16-M">2.18</unknown> <unknown tag="mrcbT16-N">Q1</unknown> <unknown tag="mrcbT16-P">89.13</unknown> <arlyear>2020</arlyear>    <unknown tag="mrcbTft">  Soubory v repozitáři: karny-508962.pdf, karny-0508962-Rights &amp; Access.pdf </unknown>    <unknown tag="mrcbU14"> 85071921926 SCOPUS </unknown> <unknown tag="mrcbU24"> PUBMED </unknown> <unknown tag="mrcbU34"> 000494883700007 WOS </unknown> <unknown tag="mrcbU63"> cav_un_epca*0256752 Information Sciences 0020-0255 1872-6291 Roč. 509 č. 1 2020 104 118 Elsevier </unknown> </cas_special> </bibitem>