This book presents state-of-the-art solution methods and applications of stochastic optimal control. It is a collection of extended papers discussed at the traditional Liverpool workshop on controlled stochastic processes with participants from both the east and the west. New problems are formulated, and progresses of ongoing research are reported. Topics covered in this book include theoretical results and numerical methods for Markov and semi-Markov decision processes, optimal stopping of Markov processes, stochastic games, problems with partial information, optimal filtering, robust control, Q-learning, and self-organizing algorithms. Real-life case studies and applications, e.g., queueing systems, forest management, control of water resources, marketing science, and healthcare, are presented. Scientific researchers and postgraduate students interested in stochastic optimal control,- as well as practitioners will find this book appealing and a valuable reference.

Presents the proceedings of the International Workshop "Modern Trends in Controlled Stochastic Processes: Theory and Applications" to be held in Liverpool in 2021 Consists of three sections fundamental theory of controlled stochastic processes (discrete and continuous time, multiple-objective optimization, finite and infinite time horizon, stochastic games, etc.), numerical methods for optimization (discretization, linear programming, approximations, swarm intelligence, evolutionary algorithms, etc.), and applications (queues, epidemiology, information transmission, medicine, inventory, water resources, chaos control, swarm robot control, etc.)

Inhalt
Average Cost Markov Decision Processes with Semi-Uniform Feller Transition Probabilities.- First Passage Exponential Optimality Problem for Semi-Markov Decision Processes.- Controlled Random Walk: Conjecture and Counter-Example.- Optimal Stopping Problems for a Family of Continuous-Time Markov Processes.- Control of Continuous-Time Markov Jump Linear Systems with PartialInformation.