Abstract
This chapter proposes an empirical approximation-estimation algorithm in difference equation game models (see Sect. 1.1.1) whose evolution is given by
where {ξ t} is a sequence of observable i.i.d. random variables defined on a probability space \(\left ( \varOmega ,\mathscr {F},P\right ) ,\) taking values in an arbitrary Borel space S, with common unknown distribution \(\theta \in \mathbb {P}(S).\)
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References
Jaśkiewicz, A., Nowak, A.: Zero-sum ergodic stochastic games with Feller transition probabilities. SIAM J. Control Optim. 45, 773–789 (2006)
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Minjárez-Sosa, J.A. (2020). Empirical Approximation-Estimation Algorithms in Markov Games. In: Zero-Sum Discrete-Time Markov Games with Unknown Disturbance Distribution. SpringerBriefs in Probability and Mathematical Statistics. Springer, Cham. https://doi.org/10.1007/978-3-030-35720-7_4
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DOI: https://doi.org/10.1007/978-3-030-35720-7_4
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