標題: Titlebook: Design of Experiments for Reinforcement Learning; Christopher Gatti Book 2015 Springer International Publishing Switzerland 2015 Kriging C [打印本頁] 作者: affected 時間: 2025-3-21 19:49
書目名稱Design of Experiments for Reinforcement Learning影響因子(影響力)
書目名稱Design of Experiments for Reinforcement Learning影響因子(影響力)學科排名
書目名稱Design of Experiments for Reinforcement Learning網(wǎng)絡公開度
書目名稱Design of Experiments for Reinforcement Learning網(wǎng)絡公開度學科排名
書目名稱Design of Experiments for Reinforcement Learning被引頻次
書目名稱Design of Experiments for Reinforcement Learning被引頻次學科排名
書目名稱Design of Experiments for Reinforcement Learning年度引用
書目名稱Design of Experiments for Reinforcement Learning年度引用學科排名
書目名稱Design of Experiments for Reinforcement Learning讀者反饋
書目名稱Design of Experiments for Reinforcement Learning讀者反饋學科排名
作者: Robust 時間: 2025-3-21 20:42 作者: 發(fā)酵 時間: 2025-3-22 03:07
Friedr. Vieweg & Sohn Verlagskatalogcal experiments. These methods are primarily based on the experimental design and the creation of metamodels of response surfaces (i.e., surrogate models that could be use replacements for true computational models).作者: 改進 時間: 2025-3-22 05:45
https://doi.org/10.1007/978-3-322-99062-4ect learning performance and what parameters are the most influential. The problem domains analyzed later in this work use very similar experimental methodologies and analysis procedures, and instead of repeating the methodology used for each problem domain, we present the methods used in this chapter.作者: 舊石器 時間: 2025-3-22 10:56
Design of Experiments,cal experiments. These methods are primarily based on the experimental design and the creation of metamodels of response surfaces (i.e., surrogate models that could be use replacements for true computational models).作者: 植物群 時間: 2025-3-22 14:31
Methodology,ect learning performance and what parameters are the most influential. The problem domains analyzed later in this work use very similar experimental methodologies and analysis procedures, and instead of repeating the methodology used for each problem domain, we present the methods used in this chapter.作者: 植物群 時間: 2025-3-22 18:34
2190-5053 by exploring what affects reinforcement learning and what cThis thesis takes an empirical approach to understanding of the behavior and interactions between the two main components of reinforcement learning: the learning algorithm and the functional representation of learned knowledge.?The author a作者: 混沌 時間: 2025-3-22 21:39
,Der Verstorbene als Gegenüber,ning process can be regarded as a process of trial-and-error, which is coupled with feedback provided from the environment that indicates the utility of the outcome. This learning method ultimately attempts to learn a mapping between actions and outcomes.作者: dilute 時間: 2025-3-23 05:24 作者: IST 時間: 2025-3-23 09:27 作者: dainty 時間: 2025-3-23 12:18
The Tandem Truck Backer-Upper Problem, truck driver in backing up the tandem trailer. The work described herein is the first to use a simple reinforcement learning approach to begin to learn the tandem trailer-backer upper problem, and we explore the ability of the temporal difference algorithm to learn this problem in this chapter.作者: 分發(fā) 時間: 2025-3-23 16:49 作者: 保守 時間: 2025-3-23 19:17
The Mountain Car Problem,lley, and the car must instead build up momentum by successively driving up opposing sides of the valley. This chapter explores the mountain car problem using sequential CART and stochastic kriging to understand the parameter space.作者: IRATE 時間: 2025-3-23 22:36
Book 2015monly employed to study machine learning methods.?The results outlined in this work provide insight as to what enables and what has an effect on successful reinforcement learning implementations so that this learning method can be applied to more challenging problems..作者: 帳單 時間: 2025-3-24 02:24
https://doi.org/10.1007/978-3-663-10109-3nforcement learning is followed by a review of the three major components of the reinforcement learning method: the environment, the learning algorithm, and the representation of the learned knowledge.作者: 神圣將軍 時間: 2025-3-24 07:08 作者: PET-scan 時間: 2025-3-24 14:18
Introduction,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 作者: subordinate 時間: 2025-3-24 15:57 作者: endarterectomy 時間: 2025-3-24 19:39 作者: 單獨 時間: 2025-3-25 00:34 作者: 五行打油詩 時間: 2025-3-25 06:21 作者: laceration 時間: 2025-3-25 09:48
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作者: heckle 時間: 2025-3-25 13:10 作者: Foreknowledge 時間: 2025-3-25 19:49 作者: 極微小 時間: 2025-3-25 21:33 作者: 濕潤 時間: 2025-3-26 01:19 作者: flimsy 時間: 2025-3-26 06:38 作者: 糾纏 時間: 2025-3-26 08:35
,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 作者: 削減 時間: 2025-3-26 15:11
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作者: 訓誡 時間: 2025-3-26 17:19
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作者: Repatriate 時間: 2025-3-26 22:38 作者: 恩惠 時間: 2025-3-27 02:12 作者: 解凍 時間: 2025-3-27 08:10 作者: Morose 時間: 2025-3-27 09:28 作者: monogamy 時間: 2025-3-27 15:08
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.作者: Leaven 時間: 2025-3-27 18:56
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.作者: craving 時間: 2025-3-27 23:24 作者: 上坡 時間: 2025-3-28 03:01 作者: 集聚成團 時間: 2025-3-28 06:45
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.作者: 沉積物 時間: 2025-3-28 12:33
