Markov Chains on Metric Spaces

Discover the fascinating world of Markov chains with Markov Chains on Metric Spaces by Michel Benaïm. Published by Springer International Publishing AG in 2022, this insightful book spans 197 pages and serves as an essential resource for graduate students and researchers in probability theory.

In this first edition, Benaïm offers a comprehensive introduction to discrete-time Markov chains that evolve on separable metric spaces. This book is designed to be the foundation of a semester- or year-long graduate course, focusing on the intricacies of Markov chains and their applications in random dynamics.

Whether you are a student looking to deepen your understanding of probability theory or a professional seeking to enhance your knowledge of Markov processes, this book is a must-have addition to your library.