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Algorithms for Omega-Regular Games with Incomplete Information
Krishnendu Chatterjee, Laurent Doyen, Tom Henzinger, Jean-Francois Raskin

Citation
Krishnendu Chatterjee, Laurent Doyen, Tom Henzinger, Jean-Francois Raskin. "Algorithms for Omega-Regular Games with Incomplete Information". Technical report, University of California, Berkeley, UCB/EECS-2006-89, June, 2006.

Abstract
We study observation-based strategies for two-player turn-based games on graphs with omega-regular objectives. An observation-based strategy relies on incomplete information about the history of a play, namely, on the past sequence of observations. Such games occur in the synthesis of a controller that does not see the private state of the plant. Our main results are twofold. First, we give a fixpoint algorithm for computing the set of states from which a player can win with a deterministic observation-based strategy for any omega-regular objective. The fixpoint is computed in the lattice of antichains of state sets. This algorithm has the advantages of being directed by the objective and of avoiding an explicit subset construction on the game graph. Second, we give an algorithm for computing the set of states from which a player can win with probability 1 with a randomized observation-based strategy for a Buchi objective. This set is of interest because in the absence of complete information, randomized strategies are more powerful than deterministic ones. We show that our algorithms are optimal by proving matching lower bounds.

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Citation formats  
  • HTML
    Krishnendu Chatterjee, Laurent Doyen, Tom Henzinger,
    Jean-Francois Raskin. <a
    href="http://chess.eecs.berkeley.edu/pubs/320.html"
    ><i>Algorithms for Omega-Regular Games with
    Incomplete Information</i></a>, Technical
    report,  University of California, Berkeley,
    UCB/EECS-2006-89, June, 2006.
  • Plain text
    Krishnendu Chatterjee, Laurent Doyen, Tom Henzinger,
    Jean-Francois Raskin. "Algorithms for Omega-Regular
    Games with Incomplete Information". Technical report, 
    University of California, Berkeley, UCB/EECS-2006-89, June,
    2006.
  • BibTeX
    @techreport{ChatterjeeDoyenHenzingerRaskin06_AlgorithmsForOmegaRegularGamesWithIncompleteInformation,
        author = {Krishnendu Chatterjee and Laurent Doyen and Tom
                  Henzinger and Jean-Francois Raskin},
        title = {Algorithms for Omega-Regular Games with Incomplete
                  Information},
        institution = {University of California, Berkeley},
        number = {UCB/EECS-2006-89},
        month = {June},
        year = {2006},
        abstract = {We study observation-based strategies for
                  two-player turn-based games on graphs with
                  omega-regular objectives. An observation-based
                  strategy relies on incomplete information about
                  the history of a play, namely, on the past
                  sequence of observations. Such games occur in the
                  synthesis of a controller that does not see the
                  private state of the plant. Our main results are
                  twofold. First, we give a fixpoint algorithm for
                  computing the set of states from which a player
                  can win with a deterministic observation-based
                  strategy for any omega-regular objective. The
                  fixpoint is computed in the lattice of antichains
                  of state sets. This algorithm has the advantages
                  of being directed by the objective and of avoiding
                  an explicit subset construction on the game graph.
                  Second, we give an algorithm for computing the set
                  of states from which a player can win with
                  probability 1 with a randomized observation-based
                  strategy for a Buchi objective. This set is of
                  interest because in the absence of complete
                  information, randomized strategies are more
                  powerful than deterministic ones. We show that our
                  algorithms are optimal by proving matching lower
                  bounds.},
        URL = {http://chess.eecs.berkeley.edu/pubs/320.html}
    }
    

Posted by Christopher Brooks on 7 Jun 2007.
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