Empirical Approximation-Estimation Algorithms in Markov Games

J. Adolfo Minjárez-Sosa*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


This chapter proposes an empirical approximation-estimation algorithm in difference equation game models (see Sect. 1.1.1) whose evolution is given by xt+1=F(xt,at,bt,ξt),t∈ℕ0, where {ξt} is a sequence of observable i.i.d. random variables defined on a probability space (Ω, F, P), taking values in an arbitrary Borel space S, with common unknown distribution θ∈ ℙ(S).

Original languageEnglish
Title of host publicationSpringerBriefs in Probability and Mathematical Statistics
PublisherSpringer Nature
Number of pages21
StatePublished - 2020

Publication series

NameSpringerBriefs in Probability and Mathematical Statistics
ISSN (Print)2365-4333
ISSN (Electronic)2365-4341

Bibliographical note

Publisher Copyright:
© 2020, The Author(s), under exclusive license to Springer Nature Switzerland AG.


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