2,615 research outputs found

    Qualitative Analysis of Concurrent Mean-payoff Games

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    We consider concurrent games played by two-players on a finite-state graph, where in every round the players simultaneously choose a move, and the current state along with the joint moves determine the successor state. We study a fundamental objective, namely, mean-payoff objective, where a reward is associated to each transition, and the goal of player 1 is to maximize the long-run average of the rewards, and the objective of player 2 is strictly the opposite. The path constraint for player 1 could be qualitative, i.e., the mean-payoff is the maximal reward, or arbitrarily close to it; or quantitative, i.e., a given threshold between the minimal and maximal reward. We consider the computation of the almost-sure (resp. positive) winning sets, where player 1 can ensure that the path constraint is satisfied with probability 1 (resp. positive probability). Our main results for qualitative path constraints are as follows: (1) we establish qualitative determinacy results that show that for every state either player 1 has a strategy to ensure almost-sure (resp. positive) winning against all player-2 strategies, or player 2 has a spoiling strategy to falsify almost-sure (resp. positive) winning against all player-1 strategies; (2) we present optimal strategy complexity results that precisely characterize the classes of strategies required for almost-sure and positive winning for both players; and (3) we present quadratic time algorithms to compute the almost-sure and the positive winning sets, matching the best known bound of algorithms for much simpler problems (such as reachability objectives). For quantitative constraints we show that a polynomial time solution for the almost-sure or the positive winning set would imply a solution to a long-standing open problem (the value problem for turn-based deterministic mean-payoff games) that is not known to be solvable in polynomial time

    Probabilistic modal {\mu}-calculus with independent product

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    The probabilistic modal {\mu}-calculus is a fixed-point logic designed for expressing properties of probabilistic labeled transition systems (PLTS's). Two equivalent semantics have been studied for this logic, both assigning to each state a value in the interval [0,1] representing the probability that the property expressed by the formula holds at the state. One semantics is denotational and the other is a game semantics, specified in terms of two-player stochastic parity games. A shortcoming of the probabilistic modal {\mu}-calculus is the lack of expressiveness required to encode other important temporal logics for PLTS's such as Probabilistic Computation Tree Logic (PCTL). To address this limitation we extend the logic with a new pair of operators: independent product and coproduct. The resulting logic, called probabilistic modal {\mu}-calculus with independent product, can encode many properties of interest and subsumes the qualitative fragment of PCTL. The main contribution of this paper is the definition of an appropriate game semantics for this extended probabilistic {\mu}-calculus. This relies on the definition of a new class of games which generalize standard two-player stochastic (parity) games by allowing a play to be split into concurrent subplays, each continuing their evolution independently. Our main technical result is the equivalence of the two semantics. The proof is carried out in ZFC set theory extended with Martin's Axiom at an uncountable cardinal

    Concurrent Constraint Calculi: a Declarative Paradigm for Modeling Music Systems.

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    Concurrent constraint programming (CCP) has emerged as a simple but powerful paradigm for concurrent systems; i.e. systems of multiple agents that interact with each other as for example in a collection of music processes (musicians) performing a particular piece. The ntcc calculus is a CCP formalism for modeling temporal reactive systems. In ntcc, processes can be constrained by temporal requirements such as delays, time-outs and pre-emptions. Thus, the calculus integrates two dimensions of computation: a horizontal dimension dealing with partial information (e.g., note > 60) and a vertical one in which temporal requirements come into play (e.g., a process must be executed at any time within the next ten time units). We shall show that the above integration is remarkably useful for modeling complex musical processes, in particular for music improvisation. For example, for the vertical dimension one can specify that a given process can nondeterministically choose any note satisfying a given constraint. For the horizontal dimension one can specify that the process can nondeterministically choose the time to play the note subject to a given time upper bound. This nondeterministic view is particularly suitable for processes representing a musician's choices when improvising. Similarly, the horizontal dimension may supply partial information on a rhythmic pattern that leaves room for variation while keeping a basic control. We shall also illustrate how implementing a weaker ntcc model of a musical process may greatly simplify the formal verification of its properties. We argue that this modeling strategy provides a "runnable specification" for music problems that eases the task of formally reasoning about them

    Stochastic concurrent constraint programming and differential equations

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    We tackle the problem of relating models of systems (mainly biological systems) based on stochastic process algebras (SPA) with models based on differential equations. We define a syntactic procedure that translates programs written in stochastic Concurrent Constraint Programming (sCCP) into a set of Ordinary Differential Equations (ODE), and also the inverse procedure translating ODE's into sCCP programs. For the class of biochemical reactions, we show that the translation is correct w.r.t. the intended rate semantics of the models. Finally, we show that the translation does not generally preserve the dynamical behavior, giving a list of open research problems in this direction
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