Empirical Approximation-Estimation Algorithms in Markov Games

J. Adolfo Minjárez-Sosa

doi:10.1007/978-3-030-35720-7_4

Empirical Approximation-Estimation Algorithms in Markov Games

J. Adolfo Minjárez-Sosa^*

^*Corresponding author for this work

Departamento de Matemáticas

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

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 {ξ_t} 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 language	English
Title of host publication	SpringerBriefs in Probability and Mathematical Statistics
Publisher	Springer Nature
Pages	47-67
Number of pages	21
DOIs	https://doi.org/10.1007/978-3-030-35720-7_4
State	Published - 2020

Publication series

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

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

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Empirical Approximation-Estimation Algorithms in Markov Games

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