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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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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 d
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,Der Verstorbene als Gegenüber,havior in this case can be defined as the set of sequential decisions that result in the achievement of a goal or the best possible outcome. This learning process can be regarded as a process of trial-and-error, which is coupled with feedback provided from the environment that indicates the utility
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https://doi.org/10.1007/978-3-663-10109-3nt learning is not very well-known and although the learning paradigm is easily understandable, some of the more detailed concepts can be difficult to grasp. Accordingly, reinforcement learning is presented beginning with a review of the the fundamental concepts and methods. This introduction to rei
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Friedr. Vieweg & Sohn Verlagskatalogview both classical and contemporary design of experiments methods. Classical methods are well-established and have a long history of use in many applications; some of these include factorial designs, ANOVA (analysis of variance), and response surface modeling amongst others. The contemporary method
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