Abstract
A procedure called hierarchically accelerated dynamic programming (HADP) is presented which, at the cost of a degree of suboptimality, can significantly accelerate dynamic programming algorithms for discrete event systems modeled by finite-state machines (FSMs). The methodology is based. upon the (possibly iterated) dynamical abstraction of a given FSM by state aggregation in order to generate a so-called partition machine hierarchy. Necessary and sufficient conditions for the HADP procedure to generate globally optimal solutions are given as well as bounds on the degree of suboptimality of the method. A group of examples called the Broken Manhattan Grid problems is used to illustrate an implementation of HADP with two and three level hierarchies. A set of open problems is described concerning the construction and selection of the partition machine abstractions and the improvement of the estimation of HADP suboptimality.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: 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.
