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Springer Stochastic Optimal Control in Infinite Dimension - HJB Equations

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Description

This comprehensive guide introduces stochastic optimal control theory in infinite-dimensional settings, delivering a complete account of second-order HJB equations in Hilbert spaces with direct applicability to stochastic optimal control problems. The book opens with foundational material on optimal stochastic control, presenting essential results including the dynamic programming principle with detailed proofs and practical application examples. It provides an authoritative, up-to-date exposition of viscosity solutions and regular solutions for second-order HJB equations in infinite dimensions. Designed for researchers and advanced students in applied mathematics and probability theory, this volume (volume 82 in the Probability Theory and Stochastic Modelling series) bridges abstract theory with concrete problem-solving techniques, making sophisticated control methods accessible to practitioners working with complex dynamical systems.

Key Features

Volume 82 in the Springer Probability Theory and Stochastic Modelling series delivers rigorous mathematical foundations for optimal control applications.

Complete exposition of second-order HJB equations in infinite-dimensional Hilbert spaces connects abstract theory to practical stochastic control problems.

Dynamic programming principle presented with full proofs enables readers to understand and apply fundamental control theory concepts.

Viscosity solutions and regular solutions theory for HJB equations provides modern analytical tools for solving optimal control challenges.

Application examples throughout the book demonstrate how theoretical results apply to real-world stochastic optimal control scenarios.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
09 September 2018
Listed Since
08 February 2019

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