scholarly journals Average optimal strategies for zero-sum Markov games with poorly known payoff function on one side

2014 ◽  
Vol 1 (1) ◽  
pp. 105-119
Author(s):  
Fernando Luque-Vásquez ◽  
◽  
J. Adolfo Minjárez-Sosa ◽  
Keyword(s):  
Optimal Strategies ◽  
Payoff Function ◽  
Markov Games ◽  
Zero Sum ◽  
Average Optimal Strategies

On zero-sum two-person undiscounted semi-Markov games with a multichain structure

2017 ◽  
Vol 49 (3) ◽  
pp. 826-849 ◽  
Author(s):  
Prasenjit Mondal
Keyword(s):  
Stochastic Game ◽  
Optimal Strategies ◽  
Markov Games ◽  
Stationary Strategies ◽  
Current State ◽  
Strategy Evaluation ◽  
Optimality Equations ◽  
Optimal Stationary Strategies ◽  
Zero Sum ◽  
Absorbing States

Abstract Zero-sum two-person finite undiscounted (limiting ratio average) semi-Markov games (SMGs) are considered with a general multichain structure. We derive the strategy evaluation equations for stationary strategies of the players. A relation between the payoff in the multichain SMG and that in the associated stochastic game (SG) obtained by a data-transformation is established. We prove that the multichain optimality equations (OEs) for an SMG have a solution if and only if the associated SG has optimal stationary strategies. Though the solution of the OEs may not be optimal for an SMG, we establish the significance of studying the OEs for a multichain SMG. We provide a nice example of SMGs in which one player has no optimal strategy in the stationary class but has an optimal semistationary strategy (that depends only on the initial and current state of the game). For an SMG with absorbing states, we prove that solutions in the game where all players are restricted to semistationary strategies are solutions for the unrestricted game. Finally, we prove the existence of stationary optimal strategies for unichain SMGs and conclude that the unichain condition is equivalent to require that the game satisfies some recurrence/ergodicity/weakly communicating conditions.

Asymptotically Optimal Strategies for Adaptive Zero-Sum Discounted Markov Games

2009 ◽  
Vol 48 (3) ◽  
pp. 1405-1421 ◽  
Author(s):  
J. Adolfo Minjárez-Sosa ◽  
Oscar Vega-Amaya
Keyword(s):  
Optimal Strategies ◽  
Asymptotically Optimal ◽  
Markov Games ◽  
Zero Sum

scholarly journals Optimal strategies for adaptive zero-sum average Markov games

2013 ◽  
Vol 402 (1) ◽  
pp. 44-56 ◽  
Author(s):  
J. Adolfo Minjárez-Sosa ◽  
Óscar Vega-Amaya
Keyword(s):  
Optimal Strategies ◽  
Markov Games ◽  
Zero Sum

Zero-sum two-person semi-Markov games

1992 ◽  
Vol 29 (01) ◽  
pp. 56-72 ◽  
Author(s):  
Arbind K. Lal ◽  
Sagnik Sinha
Keyword(s):  
Stochastic Games ◽  
Optimal Strategies ◽  
Existence Of A Solution ◽  
Average Case ◽  
Optimality Equation ◽  
Markov Games ◽  
Special Cases ◽  
Ergodic Condition ◽  
Markov Decision ◽  
Zero Sum

Semi-Markov games are investigated under discounted and limiting average payoff criteria. The issue of the existence of the value and a pair of stationary optimal strategies are settled; the optimality equation is studied and under a natural ergodic condition the existence of a solution to the optimality equation is proved for the limiting average case. Semi-Markov games provide useful flexibility in constructing recursive game models. All the work on Markov/semi-Markov decision processes and Markov (stochastic) games can be viewed as special cases of the developments in this paper.

Zero-sum two-person semi-Markov games

1992 ◽  
Vol 29 (1) ◽  
pp. 56-72 ◽  
Author(s):  
Arbind K. Lal ◽  
Sagnik Sinha
Keyword(s):  
Stochastic Games ◽  
Optimal Strategies ◽  
Existence Of A Solution ◽  
Average Case ◽  
Optimality Equation ◽  
Markov Games ◽  
Special Cases ◽  
Ergodic Condition ◽  
Markov Decision ◽  
Zero Sum

Semi-Markov games are investigated under discounted and limiting average payoff criteria. The issue of the existence of the value and a pair of stationary optimal strategies are settled; the optimality equation is studied and under a natural ergodic condition the existence of a solution to the optimality equation is proved for the limiting average case. Semi-Markov games provide useful flexibility in constructing recursive game models. All the work on Markov/semi-Markov decision processes and Markov (stochastic) games can be viewed as special cases of the developments in this paper.

Zero-Sum Markov Games with Random State-Actions-Dependent Discount Factors: Existence of Optimal Strategies

2018 ◽  
Vol 9 (1) ◽  
pp. 103-121 ◽  
Author(s):  
David González-Sánchez ◽  
Fernando Luque-Vásquez ◽  
J. Adolfo Minjárez-Sosa
Keyword(s):  
Optimal Strategies ◽  
Markov Games ◽  
Discount Factors ◽  
Zero Sum ◽  
Random State

PIVOTING ALGORITHMS FOR SOME CLASSES OF STOCHASTIC GAMES: A SURVEY

2001 ◽  
Vol 03 (02n03) ◽  
pp. 253-281 ◽  
Author(s):  
S. R. MOHAN ◽  
S. K. NEOGY ◽  
T. PARTHASARATHY
Keyword(s):  
Linear Complementarity Problem ◽  
Complementarity Problem ◽  
Stochastic Games ◽  
Optimal Strategies ◽  
Linear Complementarity ◽  
Dual Simplex Method ◽  
Special Cases ◽  
Dual Simplex ◽  
Finite Step ◽  
Zero Sum

In this paper, we survey the recent literature on computing the value vector and the associated optimal strategies of the players for special cases of zero-sum stochastic games, or in computing a Nash equilibrium point and the corresponding stationary strategies of the players for special cases of nonzero-sum stochastic games, using finite-step algorithms based on pivoting. Examples of finite-step pivoting algorithms are the various simplex-type algorithms, such as the primal simplex or dual simplex method for solving the linear programming problem or Lemke's or Lemke-Howson's algorithm for solving the linear complementarity problem. Also included are Lemke-type algorithms for solving various generalisations of the linear complementarity problem. The survey also includes a few new results and observations.

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