Cost inference of discrete-time linear quadratic control policies using human-behaviour learning

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dc.contributor.authorPerrusquía, Adolfo
dc.contributor.authorGuo, Weisi
dc.date.accessioned2022-07-06T10:47:14Z
dc.date.available2022-07-06T10:47:14Z
dc.date.issued2022-06-30
dc.description.abstractIn this paper, a cost inference algorithm for discrete-time systems using human-behaviour learning is pro-posed. The approach is inspired in the complementary learning that exhibits the neocortex, hippocampus, and striatum learning systems to achieve complex decision making. The main objective is to infer the hidden cost function from expert's data associated to the hippocampus (off-policy data) and transfer it to the neocortex for policy generalization (on-policy data) in different systems and environments. The neocortex is modelled by a Q-learning and a least-squares identification algorithms for on-policy learning and system identification. The cost inference is obtained using a one-step gradient descent rule and an inverse optimal control algorithm. Convergence of the cost inference algorithm is discussed using Lyapunov recursions. Simulations verify the effectiveness of the approach.en_UK
dc.identifier.citationPerrusquia A, Guo W. (2022) Cost inference of discrete-time linear quadratic control policies using human-behaviour learning. In: CODiT 2022: 8th International Conference on Control, Decision and Information Technologies, 17-20 May 2022, Istanbul, Turkey, pp. 165-170en_UK
dc.identifier.eisbn978-1-6654-9607-0
dc.identifier.eissn2576-3555
dc.identifier.isbn978-1-6654-9608-7
dc.identifier.issn2576-3547
dc.identifier.urihttps://doi.org/10.1109/CoDIT55151.2022.9804118
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/18152
dc.language.isoenen_UK
dc.publisherIEEEen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectLearning systemsen_UK
dc.subjectCostsen_UK
dc.subjectQ-learningen_UK
dc.subjectDecision makingen_UK
dc.subjectOptimal controlen_UK
dc.subjectCost functionen_UK
dc.subjectInference algorithmsen_UK
dc.titleCost inference of discrete-time linear quadratic control policies using human-behaviour learningen_UK
dc.typeConference paperen_UK

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