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    <title>Auteurs : Dmitrii Lozovanu</title>
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    <description>Publications of Auteurs Dmitrii Lozovanu</description>
    <language>fr</language>
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      <title>Saddle Point Conditions for Antagonistic Positional Games in Complex Markov Decision Processes</title>
      <link>https://popups.uliege.be/3041-539x/index.php?id=4641</link>
      <description>A class of stochastic antagonistic positional games for Markov decision processes with average and expected total discounted costs optimization criteria are formu lated and studied. Saddle point conditions in the considered class of games that extend saddle point conditions for deterministic parity games are derived. Further more algorithms for determining the optimal stationary strategies of the players are proposed and grounded  </description>
      <pubDate>Mon, 14 Oct 2024 15:41:10 +0200</pubDate>
      <lastBuildDate>Thu, 17 Oct 2024 11:57:01 +0200</lastBuildDate>
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      <title>An Extension of a Polynomial Time Algorithm for the Calculation of the Limit State Matrix in a Random Graph</title>
      <link>https://popups.uliege.be/3041-539x/index.php?id=3192</link>
      <description>A characterization of a simple Markov process based on a random graph theoretic structure is introduced. We propose a polynomial time algorithm for the calculation of a limit state matrix. The algorithm is based on two procedures which will be derived in this contribution. They exploit a distinguished decomposition principle of the underlying graph theoretic structure and the special property of an acyclic directed graph. </description>
      <pubDate>Wed, 11 Sep 2024 17:01:24 +0200</pubDate>
      <lastBuildDate>Wed, 11 Sep 2024 17:01:55 +0200</lastBuildDate>
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    <item>
      <title>Intelligent Network Structures and Algorithms for Solving Multiobjective Control Problems</title>
      <link>https://popups.uliege.be/3041-539x/index.php?id=2950</link>
      <description>Discrete multiobjective control problems with varying time of states transactions of dynamical system are formulated and studied. Nash equilibrium conditions for the considered problems are given and algorithms based on dynamic programming for determining optimal solutions in the sense of Nash and Pareto are proposed and proved. We exploit a certain (so-called) intelligent network structure to underline a constructive approach </description>
      <pubDate>Tue, 03 Sep 2024 15:57:55 +0200</pubDate>
      <lastBuildDate>Tue, 03 Sep 2024 15:58:06 +0200</lastBuildDate>
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