46 research outputs found

    The asymptotic value in finite stochastic games

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    We provide a direct, elementary proof for the existence of limλ0vλ\lim_{\lambda\to 0} v_{\lambda}, where vλv_{\lambda} is the value of a λ\lambda-discounted finite two-person zero-sum stochastic game

    Differential games with asymmetric and correlated information

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    Differential games with asymmetric information were introduced by Cardaliaguet (2007). As in repeated games with lack of information on both sides (Aumann and Maschler (1995)), each player receives a private signal (his type) before the game starts and has a prior belief about his opponent's type. Then, a differential game is played in which the dynamic and the payoff function depend on both types: each player is thus partially informed about the differential game that is played. The existence of the value function and some characterizations have been obtained under the assumption that the signals are drawn independently. In this paper, we drop this assumption and extend these two results to the general case of correlated types. This result is then applied to repeated games with incomplete information: the characterization of the asymptotic value obtained by Rosenberg and Sorin (2001) and Laraki (2001) for the independent case is extended to the general case.Comment: 22 page

    A uniform Tauberian theorem in optimal control

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    In an optimal control framework, we consider the value VT(x)V_T(x) of the problem starting from state xx with finite horizon TT, as well as the value Vλ(x)V_\lambda(x) of the λ\lambda-discounted problem starting from xx. We prove that uniform convergence (on the set of states) of the values VT()V_T(\cdot) as TT tends to infinity is equivalent to uniform convergence of the values Vλ()V_\lambda(\cdot) as λ\lambda tends to 0, and that the limits are identical. An example is also provided to show that the result does not hold for pointwise convergence. This work is an extension, using similar techniques, of a related result in a discrete-time framework \cite{LehSys}.Comment: 14 page

    A formula for the value of a stochastic game

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    In 1953, Lloyd Shapley defined the model of stochastic games, which were the first general dynamic model of a game to be defined, and proved that competitive stochastic games have a discounted value. In 1982, Jean-Fran\c{c}ois Mertens and Abraham Neyman proved that competitive stochastic games admit a robust solution concept, the value, which is equal to the limit of the discounted values as the discount rate goes to 0. Both contributions were published in PNAS. In the present paper, we provide a tractable formula for the value of competitive stochastic games

    Absorbing games with irrational values

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    Can an absorbing game with rational data have an irrational limit value? Yes: In this note we provide the simplest examples where this phenomenon arises. That is, the following 3×33\times 3 absorbing game A=[112120201], A = \begin{bmatrix} 1^* & 1^* & 2^* \\ 1^* & 2^* & 0\phantom{^*} \\ 2^* & 0\phantom{^*} & 1^* \end{bmatrix}, and a sequence of 2×22\times 2 absorbing games whose limit values are k\sqrt{k}, for all integer kk. Finally, we conjecture that any algebraic number can be represented as the limit value of an absorbing game

    Constant payoff in zero-sum stochastic games

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    In a zero-sum stochastic game, at each stage, two adversary players take decisions and receive a stage payoff determined by them and by a random variable representing the state of nature. The total payoff is the discounted sum of the stage payoffs. Assume that the players are very patient and use optimal strategies. We then prove that, at any point in the game, players get essentially the same expected payoff: the payoff is constant. This solves a conjecture by Sorin, Venel and Vigeral (2010). The proof relies on the semi-algebraic approach for discounted stochastic games introduced by Bewley and Kohlberg (1976), on the theory of Markov chains with rare transitions, initiated by Friedlin and Wentzell (1984), and on some variational inequalities for value functions inspired by the recent work of Davini, Fathi, Iturriaga and Zavidovique (2016
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