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A Reinforcement Learning Approach to the Internet QoS Routing Problems
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- Qian Fei
- Faculty of Engineering, Kanto Gakuin University
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- Une Hiroyuki
- Faculty of Informatics, Hiroshima Kokusai Gakuin University
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- Ikebou Shigeya
- Faculty of Informatics, Hiroshima Kokusai Gakuin University
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- Hirata Hironori
- Graduate School of Science and Technology, Chiba University
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Description
We present a new algorithm based on reinforcement learning for packet scheduling in routers with QoS requirements. In our approach, reinforcement learning is used to learn a scheduling policy in response to feedback from the network about the delay experienced by each traffic priority class. We construct a new traffic regulator with the stochastic learning automaton, which does not require prior knowledge of the statistics of each traffic flow and can adapt to changing traffic requirements and loads.
Journal
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- Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications
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Proceedings of the ISCIE International Symposium on Stochastic Systems Theory and its Applications 2005 (0), 78-83, 2005-05-05
The ISCIE Symposium on Stochastic Systems Theory and Its Applications
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Keywords
Details 詳細情報について
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- CRID
- 1390282763010471296
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- NII Article ID
- 130007377069
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- ISSN
- 21884749
- 21884730
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- Text Lang
- en
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- Data Source
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- JaLC
- Crossref
- CiNii Articles
- OpenAIRE
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- Abstract License Flag
- Disallowed