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Subgame maxmin strategies in zero-sum stochastic games with tolerance levels. (English) Zbl 1481.91018

Summary: We study subgame \(\phi \)-maxmin strategies in two-player zero-sum stochastic games with a countable state space, finite action spaces, and a bounded and universally measurable payoff function. Here, \( \phi\) denotes the tolerance function that assigns a nonnegative tolerated error level to every subgame. Subgame \(\phi \)-maxmin strategies are strategies of the maximizing player that guarantee the lower value in every subgame within the subgame-dependent tolerance level as given by \(\phi \). First, we provide necessary and sufficient conditions for a strategy to be a subgame \(\phi \)-maxmin strategy. As a special case, we obtain a characterization for subgame maxmin strategies, i.e., strategies that exactly guarantee the lower value at every subgame. Secondly, we present sufficient conditions for the existence of a subgame \(\phi \)-maxmin strategy. Finally, we show the possibly surprising result that each game admits a strictly positive tolerance function \(\phi^\ast\) with the following property: if a player has a subgame \(\phi^\ast\)-maxmin strategy, then he has a subgame maxmin strategy too. As a consequence, the existence of a subgame \(\phi \)-maxmin strategy for every positive tolerance function \(\phi\) is equivalent to the existence of a subgame maxmin strategy.

MSC:

91A15 Stochastic games, stochastic differential games
91A10 Noncooperative games
91A05 2-person games

References:

[1] Abate, A.; Redig, F.; Tkachev, I., On the effect of perturbation of conditional probabilities in total variation, Stat Probab Lett, 88, 1-8 (2014) · Zbl 1370.60006 · doi:10.1016/j.spl.2014.01.009
[2] Blackwell, D.; Ferguson, T., The big match, Ann Math Stat, 39, 159-163 (1968) · Zbl 0164.50305 · doi:10.1214/aoms/1177698513
[3] Bogachev, VI, Measure Theory (2007), Berlin: Springer, Berlin · Zbl 1120.28001 · doi:10.1007/978-3-540-34514-5
[4] Bruyère V (2017) Computer aided synthesis: a game-theoretic approach. In: Charlier E, Leroy J, Rigo M (eds) Developments in Language Theory, vol 10396. Lecture Notes in Computer Science. Springer, pp 3-35 · Zbl 1494.91033
[5] Flesch J, Herings PJJ, Maes J, Predtetchinski A (2018) Subgame maxmin strategies in zero-sum stochastic games with tolerance levels. GSBE Research Memorandum 18/20, Maastricht University, Maastricht, pp. 1-37
[6] Flesch, J.; Predtetchinski, A., On refinements of subgame perfect \(\epsilon \)-equilibrium, Int J Game Theory, 45, 523-542 (2016) · Zbl 1388.91040 · doi:10.1007/s00182-015-0468-8
[7] Flesch, J.; Predtetchinski, A.; Sudderth, W., Characterization and simplification of optimal strategies in positive stochastic games, J Appl Probab, 55, 728-741 (2018) · Zbl 1417.91072 · doi:10.1017/jpr.2018.47
[8] Flesch J, Thuijsman F, Vrieze OJ (1998) Improving strategies in stochastic games. In: Proceedings of the 37th IEEE Conference on Decision and Control, Vol 3, IEEE, pp. 2674-2679 · Zbl 0909.90284
[9] Gillette D (1957) Stochastic games with zero stop probabilities. In: Dresher M, Tucker AW, Wolfe P (eds) Contributions to the Theory of Games, vol III. Annals of Mathematics Studies, Volume 39. Princeton University Press, Princeton, New Jersey, pp 179-187 · Zbl 0078.33001
[10] Laraki, R.; Maitra, A.; Sudderth, W., Two-person zero-sum stochastic games with semicontinuous payoff, Dyn Games Appl, 3, 162-171 (2013) · Zbl 1273.91050 · doi:10.1007/s13235-012-0054-7
[11] Mailath, G.; Postlewaite, A.; Samuelson, L., Contemporaneous perfect epsilon-equilibria, Games Econ Behav, 53, 126-140 (2005) · Zbl 1117.91313 · doi:10.1016/j.geb.2005.05.002
[12] Maitra, A.; Sudderth, W., Discrete gambling and stochastic games (1996), New York: Springer, New York · Zbl 0864.90148 · doi:10.1007/978-1-4612-4002-0
[13] Maitra, A.; Sudderth, W., Finitely additive stochastic games with Borel measurable payoffs, Int J Game Theory, 27, 257-267 (1998) · Zbl 0947.91013 · doi:10.1007/s001820050071
[14] Martin, DA, The determinacy of Blackwell games, J Symb Logic, 63, 1565-1581 (1998) · Zbl 0926.03071 · doi:10.2307/2586667
[15] Mashiah-Yaakovi, A., Correlated equilibria in stochastic games with Borel measurable payoffs, Dyn Games Appl, 5, 120-135 (2015) · Zbl 1319.91029 · doi:10.1007/s13235-014-0122-2
[16] Puterman, ML, Markov decision processes, discrete stochastic dynamic programming (1994), Hoboken: Wiley, Hoboken · Zbl 0829.90134 · doi:10.1002/9780470316887
[17] Radner, R., Collusive behavior in noncooperative epsilon-equilibria of oligopolies with long but finite lives, J Econ Theory, 22, 136-154 (1980) · Zbl 0434.90015 · doi:10.1016/0022-0531(80)90037-X
[18] Rosenberg, D.; Solan, E.; Vieille, N., Stopping games with randomized strategies, Probab Theory Related Fields, 119, 433-451 (2001) · Zbl 0988.60037 · doi:10.1007/PL00008766
[19] Selten, R., Spieltheoretische Behandlung eines Oligopolmodells mit Nachfrageträgheit: Teil I: Bestimmung des dynamischen Preisgleichgewichts, Zeitschrift für die gesamte Staatswissenschaft, 121, 301-324 (1965)
[20] Solan, E.; Vieille, N., Uniform value in recursive games, Ann App Probab, 12, 1185-1201 (2002) · Zbl 1040.91018
[21] Tversky, A.; Kahneman, D., The framing of decisions and the psychology of choice, Science, 211, 453-458 (1981) · Zbl 1225.91017 · doi:10.1126/science.7455683
[22] Yeh, J., Martingales and stochastic analysis (1995), Singapore: World Scientific, Singapore · Zbl 0848.60001 · doi:10.1142/2948
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