{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:06:10Z","timestamp":1760234770701,"version":"build-2065373602"},"reference-count":33,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2021,6,8]],"date-time":"2021-06-08T00:00:00Z","timestamp":1623110400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Austrian Science Fund FWF","award":["T 1012-GBL"],"award-info":[{"award-number":["T 1012-GBL"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>OPTCON is an algorithm for the optimal control of nonlinear stochastic systems which is particularly applicable to economic models. It delivers approximate numerical solutions to optimum control (dynamic optimization) problems with a quadratic objective function for nonlinear economic models with additive and multiplicative (parameter) uncertainties. The algorithm was first programmed in C# and then in MATLAB. It allows for deterministic and stochastic control, the latter with open loop (OPTCON1), passive learning (open-loop feedback, OPTCON2), and active learning (closed-loop, dual, or adaptive control, OPTCON3) information patterns. The mathematical aspects of the algorithm with open-loop feedback and closed-loop information patterns are presented in more detail in this paper.<\/jats:p>","DOI":"10.3390\/a14060181","type":"journal-article","created":{"date-parts":[[2021,6,8]],"date-time":"2021-06-08T12:08:55Z","timestamp":1623154135000},"page":"181","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Approximately Optimal Control of Nonlinear Dynamic Stochastic Problems with Learning: The OPTCON Algorithm"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5493-1893","authenticated-orcid":false,"given":"Dmitri","family":"Blueschke","sequence":"first","affiliation":[{"name":"Department of Economics, University of Klagenfurt, 9020 Klagenfurt, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8911-8774","authenticated-orcid":false,"given":"Viktoria","family":"Blueschke-Nikolaeva","sequence":"additional","affiliation":[{"name":"Department of Economics, University of Klagenfurt, 9020 Klagenfurt, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4984-0698","authenticated-orcid":false,"given":"Reinhard","family":"Neck","sequence":"additional","affiliation":[{"name":"Department of Economics, University of Klagenfurt, 9020 Klagenfurt, Austria"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"529","DOI":"10.1109\/TAC.1971.1099818","article-title":"The role and use of the stochastic linear-quadratic-Gaussian problem in control system design","volume":"16","author":"Athans","year":"1971","journal-title":"IEEE Trans. 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