Abstract
In industrial applications, practitioners usually facea considerable complexity when optimizing operating strategiesunder uncertainty. Typical real-world problems arising in practiceare notoriously challenging from a computational viewpoint, requiring solutions to Markov Decision problems in high dimensions. In this work, we address a novel approach to obtain anapproximate solution to a certain class of problems, whose stateprocess follows a controlled linear dynamics. Our techniques isillustrated by an implementation within the statistical languageR, which we discuss by solving a typical problem arising in practice.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.