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Titlebook: Design of Experiments for Reinforcement Learning; Christopher Gatti Book 2015 Springer International Publishing Switzerland 2015 Kriging C

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31#
發(fā)表于 2025-3-26 22:38:48 | 只看該作者
32#
發(fā)表于 2025-3-27 02:12:34 | 只看該作者
33#
發(fā)表于 2025-3-27 08:10:20 | 只看該作者
34#
發(fā)表于 2025-3-27 09:28:02 | 只看該作者
35#
發(fā)表于 2025-3-27 15:08:54 | 只看該作者
Friedr. Vieweg & Sohn VerlagskatalogThis chapter summarizes the findings of this work from both a reinforcement learning perspective as well as a design of experiments perspective. We elaborate on our findings, discuss related work and extensions, note the innovations of this work, and present potential future directions for this work.
36#
發(fā)表于 2025-3-27 18:56:36 | 只看該作者
Discussion,This chapter summarizes the findings of this work from both a reinforcement learning perspective as well as a design of experiments perspective. We elaborate on our findings, discuss related work and extensions, note the innovations of this work, and present potential future directions for this work.
37#
發(fā)表于 2025-3-27 23:24:53 | 只看該作者
38#
發(fā)表于 2025-3-28 03:01:43 | 只看該作者
39#
發(fā)表于 2025-3-28 06:45:51 | 只看該作者
The Truck Backer-upper Problem,k must be backed into a specific location with a specific orientation by controlling the orientation of the wheels of the truck cab. We use sequential CART and stochastic kriging to understand how parameters of the neural network and learning algorithm affect convergence and performance in the TBU domain.
40#
發(fā)表于 2025-3-28 12:33:23 | 只看該作者
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