17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05) Network Routing Based on Reinforcement Learning in Dynamically Changing Networks Hong Kong, China November 14-November 16 ISBN: 0-7695-2488-5
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICTAI.2005.91
In this paper we propose a reinforcement learning (RL) algorithm for packet routing in computer networks with emphasis on different traffic conditions. It is shown that routing with an RL approach, considering the traffic, can result in shorter delivery time and less congestion. A simple, but rational simulation of a computer network has also been tested and the suggested algorithm has been compared with other conventional ones. At the end, it is concluded that the suggested algorithm can perform packet routing efficiently with advantage of considering the dynamics in a real network.
Index Terms:
Adaptive Routing, Traffic Control, Reinforcement Learning, Neural Network, Computer Network
Citation:
Sara Khodayari, M. J. Yazdanpanah, "Network Routing Based on Reinforcement Learning in Dynamically Changing Networks," ictai, pp.362-366, 17th IEEE International Conference on Tools with Artificial Intelligence (ICTAI'05), 2005 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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