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This monograph opens up new horizons for engineers and researchers in academia and in industry dealing with or interested in new developments in the field of sy
Efficient Reinforcement Learning Using Gaussian Processes
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This book examines Gaussian processes in both model-based reinforcement learning (RL) and inference in nonlinear dynamic systems.First, we introduce PILCO, a fu
Neural Networks for Modelling and Control of Dynamic Systems
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Modelling and Parameter Estimation of Dynamic Systems
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This book presents a detailed examination of the estimation techniques and modeling problems. The theory is furnished with several illustrations and computer pr