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

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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.

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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.

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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..

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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.

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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

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