Matches in SemOpenAlex for { <https://semopenalex.org/work/W3168545362> ?p ?o ?g. }
Showing items 1 to 45 of
45
with 100 items per page.
- W3168545362 abstract "This paper considers the optimal control problem of a small nonlinear econometric model under parameter uncertainty and passive learning (open-loop feedback). Traditionally, this type of problems has been approached by applying linear-quadratic optimization algorithms. However, the literature demonstrated that those methods are very sensitive to the choice of random seeds producing frequently very large objective function values (outliers). Furthermore, to apply those established methods the original nonlinear problem must be linearized first, which runs the risk of solving already a different problem. Following a recent study by Savin and Blueschke (2016) in explicitly addressing parameter uncertainty with a large Monte Carlo experiment of possible realizations of the uncertain parameter and minimizing it with the Differential Evolution algorithm, we extend this approach to the case of passive learning. Our conjecture is that the evolutionary approach can provide more robust results demonstrating greater benefit from learning, while at the same time does not require to modify the original nonlinear problem at hand. Our first results support this conjecture pointing to promising results in applying heuristic optimization methods to passive and active learning in optimal control research." @default.
- W3168545362 created "2021-06-22" @default.
- W3168545362 creator A5023491376 @default.
- W3168545362 creator A5025144355 @default.
- W3168545362 creator A5075163271 @default.
- W3168545362 date "2018-01-01" @default.
- W3168545362 modified "2023-09-23" @default.
- W3168545362 title "An Evolutionary Approach to Passive Learning in Optimal Control Problems" @default.
- W3168545362 doi "https://doi.org/10.2139/ssrn.3308154" @default.
- W3168545362 hasPublicationYear "2018" @default.
- W3168545362 type Work @default.
- W3168545362 sameAs 3168545362 @default.
- W3168545362 citedByCount "1" @default.
- W3168545362 countsByYear W31685453622019 @default.
- W3168545362 crossrefType "journal-article" @default.
- W3168545362 hasAuthorship W3168545362A5023491376 @default.
- W3168545362 hasAuthorship W3168545362A5025144355 @default.
- W3168545362 hasAuthorship W3168545362A5075163271 @default.
- W3168545362 hasBestOaLocation W31685453622 @default.
- W3168545362 hasConcept C154945302 @default.
- W3168545362 hasConcept C2775924081 @default.
- W3168545362 hasConcept C41008148 @default.
- W3168545362 hasConceptScore W3168545362C154945302 @default.
- W3168545362 hasConceptScore W3168545362C2775924081 @default.
- W3168545362 hasConceptScore W3168545362C41008148 @default.
- W3168545362 hasLocation W31685453621 @default.
- W3168545362 hasLocation W31685453622 @default.
- W3168545362 hasLocation W31685453623 @default.
- W3168545362 hasLocation W31685453624 @default.
- W3168545362 hasOpenAccess W3168545362 @default.
- W3168545362 hasPrimaryLocation W31685453621 @default.
- W3168545362 hasRelatedWork W2096946506 @default.
- W3168545362 hasRelatedWork W2350741829 @default.
- W3168545362 hasRelatedWork W2358668433 @default.
- W3168545362 hasRelatedWork W2376932109 @default.
- W3168545362 hasRelatedWork W2382290278 @default.
- W3168545362 hasRelatedWork W2390279801 @default.
- W3168545362 hasRelatedWork W2748952813 @default.
- W3168545362 hasRelatedWork W2899084033 @default.
- W3168545362 hasRelatedWork W3004735627 @default.
- W3168545362 hasRelatedWork W3107474891 @default.
- W3168545362 isParatext "false" @default.
- W3168545362 isRetracted "false" @default.
- W3168545362 magId "3168545362" @default.
- W3168545362 workType "article" @default.