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Optimal Control with Learning on the Fly: System with Unknown Drift
Daniel Gurevich
, Debdipta Goswami
,
Charles L. Fefferman
,
Clarence W. Rowley
Mathematics
Mechanical & Aerospace Engineering
Princeton Institute for Computational Science and Engineering
Research output
:
Contribution to journal
›
Conference article
›
peer-review
2
Scopus citations
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Keyphrases
Additive Control
50%
Asymptotic Performance
50%
Bayesian Strategy
100%
Control Input
50%
Control Strategy
100%
Controller
50%
Drift Parameter
100%
Dynamical Model
50%
Finite Time Horizon
50%
Full Knowledge
50%
Gaussian Noise
50%
Infinite Time Horizon
50%
Large Classes
50%
Linear Observation Model
50%
Near-optimal Control
50%
On the Fly
100%
Optimal Control
100%
Optimal Control Strategy
100%
Optimal Controller
50%
Physical Systems
50%
Quadratic Cost Function
50%
Regret
50%
Stochastic Dynamical Systems
50%
Unexpected Change
50%
Worst-case Regret
50%
Mathematics
Asymptotics
33%
Bayesian
66%
Cost Function
33%
drift parameter μ
66%
Dynamical Model
33%
Dynamical System
33%
Finite Time
33%
Gaussian Distribution
33%
Minimizes
66%
Optimal Control Theory
100%
Physical System
33%
Stochastics
33%
Worst Case
33%
Engineering
Control Input
25%
Control Strategy
100%
Cost Function
25%
Finite Time
25%
Gaussian White Noise
25%
Infinite Time
25%
Observation Model
25%
Optimal Control
100%
Optimal Controller
25%
Physical System
25%
Quadratic Cost
25%
Computer Science
Control Strategy
100%
Dynamical System
25%
Gaussian White Noise
25%
Physical System
25%
Unknown Parameter
25%