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Determining policy for a system dynamics model using reinforcement learning

Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, System Design and Management Program, September, 2020 / Cataloged from the official version of thesis. / Includes bibliographical references (pages 42-43). / System dynamics allows managers and policy makers to analyze problems with non-linear feedback structures and thus counter-intuitive behavior. A main tool of system dynamics is to build a computational model of a system and analyze it to determine suitable policies to move the system to a desired goal. This work aims at using methods and algorithms from reinforcement learning to determine suitable policies for a system dynamics model. We introduce the techniques, methods and algorithms of reinforcement learning and apply them to a classical model from the system dynamics literature. / by Aditya Thomas. / S.M. in Engineering and Management / S.M.inEngineeringandManagement Massachusetts Institute of Technology, System Design and Management Program

Identiferoai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/132832
Date January 2020
CreatorsThomas, Aditya.
ContributorsMassachusetts Institute of Technology. Engineering and Management Program., System Design and Management Program., Massachusetts Institute of Technology. Engineering and Management Program
PublisherMassachusetts Institute of Technology
Source SetsM.I.T. Theses and Dissertation
LanguageEnglish
Detected LanguageEnglish
TypeThesis
Format91 pages, application/pdf
RightsMIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided., http://dspace.mit.edu/handle/1721.1/7582

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