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...
Saved in:
| Main Author: | |
|---|---|
| Format: | Book Chapter |
| Published: |
KIT Scientific Publishing
2010
|
| Subjects: | |
| Online Access: | Get Fullteks DOAB: description of the publication |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| LEADER | 01561naaaa2200289uu 4500 | ||
|---|---|---|---|
| 001 | doab_20_500_12854_45907 | ||
| 005 | 20210211 | ||
| 020 | |a KSP/1000019799 | ||
| 020 | |a 9783866445697 | ||
| 024 | 7 | |a 10.5445/KSP/1000019799 |c doi | |
| 041 | 0 | |a English | |
| 042 | |a dc | ||
| 100 | 1 | |a Deisenroth, Marc Peter |4 auth | |
| 245 | 1 | 0 | |a Efficient Reinforcement Learning using Gaussian Processes |
| 260 | |b KIT Scientific Publishing |c 2010 | ||
| 300 | |a 1 electronic resource (IX, 205 p. p.) | ||
| 506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
| 520 | |a 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. | ||
| 540 | |a Creative Commons |f https://creativecommons.org/licenses/by-nc-nd/4.0/ |2 cc |4 https://creativecommons.org/licenses/by-nc-nd/4.0/ | ||
| 546 | |a English | ||
| 653 | |a autonomous learning | ||
| 653 | |a Gaussian processes | ||
| 653 | |a control | ||
| 653 | |a machine learning | ||
| 653 | |a Bayesian inference | ||
| 856 | 4 | 0 | |a www.oapen.org |u https://www.ksp.kit.edu/9783866445697 |7 0 |z Get Fullteks |
| 856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/45907 |7 0 |z DOAB: description of the publication |