Bayesian learning for data-efficient control
Applications to learn control of unfamiliar dynamical systems with increasing autonomy are ubiquitous. From robotics, to finance, to industrial processing, autonomous learning helps obviate a heavy reliance on experts for system identification and controller design. Often real world systems are nonl...
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University of Cambridge
2017
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| Online Access: | http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.727599 |