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Efficient Reinforcement Learning using Gaussian Processes

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Book Series: Karlsruhe Series on Intelligent Sensor-Actuator-Systems / Karlsruher Institut für Technologie, Intelligent Sensor-Actuator-Systems Laboratory ISSN: 18673813 ISBN: 9783866445697 Year: Volume: 9 Pages: IX, 205 p. DOI: 10.5445/KSP/1000019799 Language: ENGLISH
Publisher: KIT Scientific Publishing
Subject: Computer Science
Added to DOAB on : 2019-07-30 20:02:01
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Abstract

This book examines Gaussian processes in both model-based reinforcement learning (RL) and inference in nonlinear dynamic systems.First, we introduce PILCO, a fully Bayesian approach for efficient RL in continuous-valued state and action spaces when no expert knowledge is available. PILCO takes model uncertainties consistently into account during long-term planning to reduce model bias. Second, we propose principled algorithms for robust filtering and smoothing in GP dynamic systems.

Fahrerabsichtserkennung und Risikobewertung für warnende Fahrerassistenzsysteme

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Book Series: Schriftenreihe / Institut für Mess- und Regelungstechnik, Karlsruher Institut für Technologie ISSN: 16134214 ISBN: 9783731505082 Year: Volume: 034 Pages: XX, 159 p. DOI: 10.5445/KSP/1000053685 Language: GERMAN
Publisher: KIT Scientific Publishing
Subject: Technology (General)
Added to DOAB on : 2019-07-30 20:02:02
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Abstract

To avoid accidents, warning driver assistance systems require an on-line estimation of the current risk of collision. For that, a new method is proposed that – in principle – is able to deal with arbitrary traffic situations. This is achieved by the use of generative models to describe the expected driver behavior. Corresponding user studies in real traffic show promising results even when real time constraints are taken into account.

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