Efficient Reinforcement Learning using Gaussian Processes

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...

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Détails bibliographiques

Auteur principal:	Deisenroth, Marc Peter
Format:	Online
Langue:	anglais
Publié:	KIT Scientific Publishing 2021
Sujets:	QA75.5-76.95 autonomous learning Gaussian processes control machine learning Bayesian inference bic Book Industry Communication::U Computing & information technology::UY Computer science
Accès en ligne:	35389
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