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Multi-agent Learning and Control System Using Ants Colony for Packet Scheduling in Routers

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Managing Next Generation Networks and Services (APNOMS 2007)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 4773))

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Abstract

This paper describes a novel method of achieving packet scheduling in several routers of network, in order to optimize the end to end delay. We use a multi-agent system to model this problem, where each agent of this system tries to optimize the local scheduling and through a communication with each other, attempts to make global coordination in order to optimize the total scheduling. The communication between agents is done by mobile agents like ants colony. A pheromone-Q learning approach is presented in this paper, which consists to applying the standard Q-learning technique adapted to our architecture with a synthetic pheromone that acts as a communication medium speeding up the learning process of cooperating agents.

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Shingo Ata Choong Seon Hong

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© 2007 Springer-Verlag Berlin Heidelberg

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Bourenane, M., Benhamamouch, D., Mellouk, A. (2007). Multi-agent Learning and Control System Using Ants Colony for Packet Scheduling in Routers. In: Ata, S., Hong, C.S. (eds) Managing Next Generation Networks and Services. APNOMS 2007. Lecture Notes in Computer Science, vol 4773. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75476-3_71

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  • DOI: https://doi.org/10.1007/978-3-540-75476-3_71

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-75475-6

  • Online ISBN: 978-3-540-75476-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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