Efficient Reinforcement Learning Using Gaussian Processes
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Efficient Reinforcement Learning Using Gaussian Processes
Author | : Marc Peter Deisenroth |
Publisher | : KIT Scientific Publishing |
Total Pages | : 226 |
Release | : 2010 |
Genre | : Electronic computers. Computer science |
ISBN | : 3866445695 |
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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 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.
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