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Efficient Reinforcement Learning using Gaussian Processes

Av: Medverkande: Materialtyp: ArtikelSerie: Utgivningsinformation: KIT Scientific Publishing 2010Beskrivning: 1 electronic resource (IX, 205 p. p.)Innehållstyp:
  • text
Medietyp:
  • computer
Bärartyp:
  • online resource
ISBN:
  • 9783866445697
Ämnen: Onlineresurser: Sammanfattning: 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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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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eng

Freely available e-book