Produkt
KlappentextThis 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.
Details
ISBN/GTIN978-3-86644-569-7
ProduktartBuch
EinbandartKartoniert, Paperback
Erscheinungsjahr2010
Erscheinungsdatum22.11.2010
Seiten205 Seiten
SpracheEnglisch
Gewicht400 g
IllustrationenIll., graph. Darst.
Artikel-Nr.11538197
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