Design of Experiments for Reinforcement Learning

This 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 approaches these entities using design of experiments not com...

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Tác giả chính:	Gatti, Christopher
Định dạng:	Sách
Ngôn ngữ:	English
Được phát hành:	Springer 2015
Những chủ đề:	Reinforcement learning Artificial intelligence Computer Literacy
Truy cập trực tuyến:	https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/57797
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spelling	oai:scholar.dlu.edu.vn:DLU123456789-577972023-11-11T05:51:55Z Design of Experiments for Reinforcement Learning Gatti, Christopher Reinforcement learning Artificial intelligence Computer Literacy This 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 approaches these entities using design of experiments not commonly 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. 2015-08-27T02:29:12Z 2015-08-27T02:29:12Z 2015 Book 978-3-319-12197-0 https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/57797 en application/pdf Springer
institution	Thư viện Trường Đại học Đà Lạt
collection	Thư viện số
language	English
topic	Reinforcement learning Artificial intelligence Computer Literacy
spellingShingle	Reinforcement learning Artificial intelligence Computer Literacy Gatti, Christopher Design of Experiments for Reinforcement Learning
description	This 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 approaches these entities using design of experiments not commonly 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.
format	Book
author	Gatti, Christopher
author_facet	Gatti, Christopher
author_sort	Gatti, Christopher
title	Design of Experiments for Reinforcement Learning
title_short	Design of Experiments for Reinforcement Learning
title_full	Design of Experiments for Reinforcement Learning
title_fullStr	Design of Experiments for Reinforcement Learning
title_full_unstemmed	Design of Experiments for Reinforcement Learning
title_sort	design of experiments for reinforcement learning
publisher	Springer
publishDate	2015
url	https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/57797
_version_	1782534823163723776

Design of Experiments for Reinforcement Learning

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