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		<identifier>oai:zbc.uz.zgora.pl:57526</identifier>
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<dc:title xml:lang="pl"><![CDATA[Colored decision process Petri nets: Modeling, analysis and stability]]></dc:title>
<dc:creator><![CDATA[Clempner, Julio]]></dc:creator>
<dc:subject xml:lang="pl"><![CDATA[decision process]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[colored Petri nets]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[colored decision process Petri nets]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[stability]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[Lyapunov methods]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[optimization]]></dc:subject>
<dc:subject xml:lang="pl"><![CDATA[game theory]]></dc:subject>
<dc:description xml:lang="pl"><![CDATA[In this paper we introduce a new modeling paradigm for developing a decision process representation called the Colored Decision Process Petri Net (CDPPN). It extends the Colored Petri Net (CPN) theoretic approach including Markov decision processes. CPNs are used for process representation taking advantage of the formal semantic and the graphical display.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[A Markov decision process is utilized as a tool for trajectory planning via a utility function. The main point of the CDPPN is its ability to represent the mark-dynamic and trajectory-dynamic properties of a decision process. Within the mark-dynamic properties framework we show that CDPPN theoretic notions of equilibrium and stability are those of the CPN.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[In the trajectory-dynamic properties framework, we optimize the utility function used for trajectory planning in the CDPPN by a Lyapunov-like function, obtaining as a result new characterizations for final decision points (optimum point) and stability.]]></dc:description>
<dc:description xml:lang="pl"><![CDATA[Moreover, we show that CDPPN mark-dynamic and Lyapunov trajectory-dynamic properties of equilibrium, stability and final decision points converge under certain restrictions. We propose an algorithm for optimum trajectory planning that makes use of the graphical representation (CPN) and the utility function. Moreover, we consider some results and discuss possible directions for further research.]]></dc:description>
<dc:publisher><![CDATA[Zielona Góra: Uniwersytet Zielonogórski]]></dc:publisher>
<dc:contributor><![CDATA[Korbicz, Józef (1951- ) - red.]]></dc:contributor>
<dc:contributor><![CDATA[Uciński, Dariusz - red.]]></dc:contributor>
<dc:date><![CDATA[2005]]></dc:date>
<dc:type xml:lang="pl"><![CDATA[artykuł]]></dc:type>
<dc:identifier><![CDATA[http://www.zbc.uz.zgora.pl/repozytorium/Content/57526/AMCS_2005_15_3_9.pdf]]></dc:identifier>
<dc:identifier><![CDATA[https://zbc.uz.zgora.pl/repozytorium/dlibra/publication/64084/edition/57526/content]]></dc:identifier>
<dc:identifier><![CDATA[oai:zbc.uz.zgora.pl:57526]]></dc:identifier>
<dc:source xml:lang="pl"><![CDATA[AMCS, volume 15, number 3 (2005)]]></dc:source>
<dc:source xml:lang="pl"><![CDATA[https://www.amcs.uz.zgora.pl/?action=paper&paper=258]]></dc:source>
<dc:language><![CDATA[eng]]></dc:language>
<dc:relation><![CDATA[oai:zbc.uz.zgora.pl:publication:64084]]></dc:relation>
<dc:rights xml:lang="pl"><![CDATA[Biblioteka Uniwersytetu Zielonogórskiego]]></dc:rights>
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