Zero-Sum Discrete-Time Markov Games with Unknown Disturbance Distribution

“This is a well written book that maintains a balance between theory and numerical examples. Each chapter is interesting and useful for the readers. This book can be recommended as a valuable material for both self study and teaching purposes, but because of its rigorous style it works also as a valuable reference for research purposes.” (Samir Kumar Neogy, zbMATH 1454.91004, 2021)

• Zero-sum Markov games.- Discounted optimality criterion.- Average payoff criterion.- Empirical approximation-estimation algorithms in Markov games.- Difference-equation games: examples.- Elements from analysis.- Probability measures and weak convergence.- Stochastic kernels.- Review on density estimation.