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<bibitem type="J">   <ARLID>0525231</ARLID> <utime>20240103224203.4</utime><mtime>20200623235959.9</mtime>   <SCOPUS>85085607647</SCOPUS> <WOS>000540349700008</WOS>  <DOI>10.1016/j.sysconle.2020.104719</DOI>           <title language="eng" primary="1">Axiomatisation of Fully Probabilistic Design Revisited</title>  <specification> <page_count>13 s.</page_count> <media_type>P</media_type> </specification>   <serial><ARLID>cav_un_epca*0257642</ARLID><ISSN>0167-6911</ISSN><title>Systems and Control Letters</title><part_num/><part_title/><volume_id>141</volume_id><volume/><publisher><place/><name>Elsevier</name><year/></publisher></serial>    <keyword>Closed-loop control</keyword>   <keyword>Control theory</keyword>   <keyword>Stochastic control</keyword>   <keyword>Stochastic modelling</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> <garant>K</garant> <fullinstit>Ústav teorie informace a automatizace AV ČR, v. v. i.</fullinstit> </author>   <source> <url>http://library.utia.cas.cz/separaty/2020/AS/karny-0525231.pdf</url> </source> <source> <url>https://www.sciencedirect.com/science/article/pii/S0167691120301006</url>  </source>        <cas_special> <project> <project_id>LTC18075</project_id> <agency>GA MŠk</agency> <country>CZ</country> <ARLID>cav_un_auth*0372050</ARLID> </project> <project> <project_id>CA16228</project_id> <agency>The European Cooperation in Science and Technology (COST)</agency> <country>XE</country> <ARLID>cav_un_auth*0372051</ARLID> </project>  <abstract language="eng" primary="1">Fully probabilistic design (FPD) of control strategies models both the closed control loop and control objectives by joint probabilities of involved variables. It selects the optimal strategy as the minimiser of Kullback–Leibler (KL) divergence of the closed-loop model to its ideal counterpart expressing the control objectives. Since its proposal (Kárný, 1996) and general algorithmisation (Kárný and Guy, 2006), FPD has been axiomatised (Kárný and Kroupa, 2012) and successfully applied both theoretically (Kárný and Guy, 2012) and practically (Quinn et al., 2003. Kárný et al., 2006)[1]. This paper refines the FPD axiomatisation and bridges FPD to standard stochastic control theory, which it encompasses, in a better way. This enhances applicability of both as well as of its popular, independently proposed, special case known as KL control (Guan et al., 2014).</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 20231122145000.8 </unknown> <inst_support> RVO:67985556 </inst_support>  <permalink>http://hdl.handle.net/11104/0309413</permalink>  <unknown tag="mrcbC61"> 1 </unknown>  <confidential>S</confidential>  <contract> <name>Publishing Agreement</name> <date>20200601</date> </contract> <article_num> 104719 </article_num> <unknown tag="mrcbC86"> 3+4 Article Automation Control Systems|Operations Research Management Science </unknown> <unknown tag="mrcbC91"> C </unknown>         <unknown tag="mrcbT16-e">OPERATIONSRESEARCH&amp;MANAGEMENTSCIENCE|AUTOMATION&amp;CONTROLSYSTEMS</unknown> <unknown tag="mrcbT16-f">3.085</unknown> <unknown tag="mrcbT16-g">0.617</unknown> <unknown tag="mrcbT16-h">10.9</unknown> <unknown tag="mrcbT16-i">0.0092</unknown> <unknown tag="mrcbT16-j">1.284</unknown> <unknown tag="mrcbT16-k">8940</unknown> <unknown tag="mrcbT16-q">154</unknown> <unknown tag="mrcbT16-s">1.289</unknown> <unknown tag="mrcbT16-y">28.44</unknown> <unknown tag="mrcbT16-x">3.24</unknown> <unknown tag="mrcbT16-3">1388</unknown> <unknown tag="mrcbT16-4">Q1</unknown> <unknown tag="mrcbT16-5">2.667</unknown> <unknown tag="mrcbT16-6">154</unknown> <unknown tag="mrcbT16-7">Q2</unknown> <unknown tag="mrcbT16-B">71.781</unknown> <unknown tag="mrcbT16-C">53.7</unknown> <unknown tag="mrcbT16-D">Q2</unknown> <unknown tag="mrcbT16-E">Q1</unknown> <unknown tag="mrcbT16-M">0.71</unknown> <unknown tag="mrcbT16-N">Q2</unknown> <unknown tag="mrcbT16-P">58.929</unknown> <arlyear>2020</arlyear>    <unknown tag="mrcbTft">  Soubory v repozitáři: karny-0525231-SCL104719.html </unknown>    <unknown tag="mrcbU14"> 85085607647 SCOPUS </unknown> <unknown tag="mrcbU24"> PUBMED </unknown> <unknown tag="mrcbU34"> 000540349700008 WOS </unknown> <unknown tag="mrcbU63"> cav_un_epca*0257642 Systems and Control Letters 0167-6911 1872-7956 Roč. 141 č. 1 2020 Elsevier </unknown> </cas_special> </bibitem>