Learning to Schedule Network Resources Throughput and Delay Optimally Using Q⁺-Learning

Trends in technology lead to an increasing of their role in the development of humanity. Exactly “cloud technologies”, which are the basis for the technological development of the information society now, also they play the role of the leading tool of informatization of education, especially united with “edutainment”.During the development and implementation of software and network technologies in professional artistic education, the following issues remain unsolved: the provision of modern computer equipment and software, technical support for the stable work of information products, and the provision of selective authorized access for students to specific network resources. The methodology based on “cloud calculates” technology provides an opportunity to overcome these difficulties. And the last, but not at least, students may be attracted to the most promising areas of the development of modern information products.Actuality, practical significance, and insufficient development of these problems caused the choice of the topic of our research: “Terms of use of “edutainment” and “cloud technologies” in professional artistic education “.The aim of the research is to determine the conditions of the use of “edutainment” and “cloud technologies” in the preparation of future teachers of musical art.Methods of research: analysis of psychological and pedagogical literature in order to determine the state of development of the problem; synthesis, comparison, generalization for justifying the concepts of “edutainment” and “cloud technologies” and methods of their use in the educational process.This article deals with issues of the use of edutainment technologies and “cloud technologies”. It is offered conditions of using edutainment and “cloud technologies” in post-nonclassical professional art education on the example of subject “Musical Art”. Actual “cloud” services are analyzed and examples of their integration to educational process of professional art establishments are proposed.

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Q-learning System Based on Cooperative Least Squares Support Vector Machine

ACTA AUTOMATICA SINICA ◽

10.3724/sp.j.1004.2009.00214 ◽

2009 ◽

Vol 35 (2) ◽

pp. 214-219 ◽

Cited By ~ 3

Author(s):

Xue-Song WANG ◽

Xi-Lan TIAN ◽

Yu-Hu CHENG ◽

Jian-Qiang YI

Keyword(s):

Support Vector Machine ◽

Least Squares ◽

Learning System ◽

Support Vector ◽

Q Learning

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Application of improved Q learning algorithm to job shop problem

Journal of Computer Applications ◽

10.3724/sp.j.1087.2008.03268 ◽

2009 ◽

Vol 28 (12) ◽

pp. 3268-3270

Author(s):

Chao WANG ◽

Jing GUO ◽

Zhen-qiang BAO

Keyword(s):

Job Shop ◽

Learning Algorithm ◽

Q Learning

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