{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/132832"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/132832","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Determining policy for a system dynamics model using reinforcement learning","abstract":"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. 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