Neural Approximations for Optimal Control and Decision, 1st ed. 2020 Communications and Control Engineering Series

Neural Approximations for Optimal Control and Decision provides a comprehensive methodology for the approximate solution of functional optimization problems using neural networks and other nonlinear approximators where the use of traditional optimal control tools is prohibited by complicating factors like non-Gaussian noise, strong nonlinearities, large dimension of state and control vectors, etc.

Features of the text include:

? a general functional optimization framework;

? thorough illustration of recent theoretical insights into the approximate solutions of complex functional optimization problems;

? comparison of classical and neural-network based methods of approximate solution;

? bounds to the errors of approximate solutions;

? solution algorithms for optimal control and decision in deterministic or stochastic environments with perfect or imperfect state measurements over a finite or infinite time horizon and with one decision maker or several;

? applications of current interest: routing in communications networks, traffic control, water resource management, etc.; and

? numerous, numerically detailed examples.

The authors? diverse backgrounds in systems and control theory, approximation theory, machine learning, and operations research lend the book a range of expertise and subject matter appealing to academics and graduate students in any of those disciplines together with computer science and other areas of engineering.

Chapter 1. The Basic Infinite-Dimensional or Functional Optimization Problem.- Chapter 2. From Functional Optimization to Nonlinear Programming by the Extended Ritz Method.- Chapter 3. Some Families of FSP Functions and Their Properties.- Chapter 4. Design of Mathematical Models by Learning from Data and FSP Functions.- Chapter 5. Numerical Methods for Integration and Search for Minima.- Chapter 6. Deterministic Optimal Control Over a Finite Horizon.- Chapter 7. Stochastic Optimal Control with Perfect State Information over a Finite Horizon.- Chapter 8. Stochastic Optimal Control with Imperfect State Information over a Finite Horizon.- Chapter 9. Team Optimal Control Problems.- Chapter 10. Optimal Control Problems over an Infinite Horizon.- Index.

Riccardo Zoppoli received the "Laurea" degree in electronic engineering from the University of Genoa, Italy, in 1965, and the title of "Libero Docente" in 1971. From 1968 to 1979, he was an Associate Professor of Control Theory at the University of Genoa. Since 1980, he has been Full Professor of Control Theory and Operations Research at the same University. In 1972, was a NATO Visiting Scholar at the University of California at Los Angeles. From 1979 to 1985, he was responsible for the special project "Distributed Process Control Systems" supported by the National Research Council of Italy. He is the author of more than 100 papers scientific papers in the area of systems theory and operations research. His more recent research interests include large-scale systems, team theory, optimal control and filtering, and neural approximations. Prof. Zoppoli has served on various national and international and academic committees and as member of several boards of technical boards. In 2017, he received the title of "Professor Emeritus" from University of Genova, Italy.

Marcello Sanguineti  was born in Chiavari (Genoa), Italy. He received the ``Laurea'' (MSc) degree cum laude in Electronic Engineering and the PhD degree in Electronic Engineering and Computer Science, both from the University of Genova (Italy). He is currently Associate Professor of Operations Research at the University of Genova, with National Scientific Qualification as Full Professor, where he teaches "Operations Research", "Optimization Techniques" and "Strategic Choices: Games and Team Optimization". He is also Research Associate at CNR-INM (Institute for Marine Engineering) and Guest Scholar at IMT - School for Advances Studies (Lucca, Italy). Previously he was Research Associate at CNR-ISSIA (Institute of Intelligent Systems for Automation). He was member of the Scientific Boards of several PhD programs at the University of Genova, currently the PhD program in Comp

Material is an up-to-date treatment of optimal control problems which have thus far been difficult to solve

Applications selected have major current interest: routing in communications networks, freeway traffic control, water resources management, etc

Authors with backgrounds in automatic control, systems theory and operations research lend the book a breadth of approach which makes the methods described applicable in many circumstances