Neural Approximations for Optimal Control and Decision
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
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Riccardo Zoppoli Marcello Sanguineti Giorgio Gnecco Thomas Parisini
Neural Approximations for Optimal Control and Decision
Communications and Control Engineering Series Editors Alberto Isidori, Roma, Italy Jan H. van Schuppen, Amsterdam, The Netherlands Eduardo D. Sontag, Boston, USA Miroslav Krstic, La Jolla, USA
Communications and Control Engineering is a high-level academic monograph series publishing research in control and systems theory, control engineering and communications. It has worldwide distribution to engineers, researchers, educators (several of the titles in this series find use as advanced textbooks although that is not their primary purpose), and libraries. The series reflects the major technological and mathematical advances that have a great impact in the fields of communication and control. The range of areas to which control and systems theory is applied is broadening rapidly with particular growth being noticeable in the fields of finance and biologically-inspired control. Books in this series generally pull together many related research threads in more mature areas of the subject than the highly-specialised volumes of Lecture Notes in Control and Information Sciences. This series’s mathematical and control-theoretic emphasis is complemented by Advances in Industrial Control which provides a much more applied, engineering-oriented outlook. Indexed by SCOPUS and Engineering Index. Publishing Ethics: Researchers should conduct their research from research proposal to publication in line with best practices and codes of conduct of relevant professional bodies and/or national and international regulatory bodies. For more details on individual ethics matters please see: https://www.springer.com/gp/authors-editors/journal-author/journal-authorhelpdesk/publishing-ethics/14214
More information about this series at http://www.springer.com/series/61
Riccardo Zoppoli Marcello Sanguineti Giorgio Gnecco Thomas Parisini •
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Neural Approximations for Optimal Control and Decision
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Riccardo Zoppoli DIBRIS Università di Genova Genoa, Italy
Marcello Sanguineti DIBRIS Università di Genova Genoa, Italy
Giorgio Gnecco AXES Research Unit IMT—School of Advanced Studies Lucca Lucca, Italy
Thomas Parisini Imperial College London London, UK University of Trieste Trieste, Italy
ISSN 0178-5354 ISSN 2197-7119 (electronic) Communications and Control Engineering ISBN 978-3-030-29691-9 ISBN 978-3-030-29693-3 (eBook) https://doi.org/10.1007/978-3-030-29693-3 © Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, tra
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