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Interactive Mobile Communication, Technologies and Learning

IMCL 2017: Interactive Mobile Communication Technologies and Learning pp 952–968Cite as

Cooperative Learning-Agents for Task Allocation Problem

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 725))

Abstract

In this paper, we will present a working methodology for solving the task allocation problem in a multi-robot system, i.e. assign the tasks being performed to appropriate robots. In fact, the proposed approach combines the advantages of several well-known algorithms (e.g. quantum genetic algorithms, Q-learning machine-learning, etc.), in order to construct a good solution for the task allocation problem.

Besides, the proposed working methodology has been implemented using the Java programming language and the JADE multi-agent platform; also it has been simulated on a real-life scenario, which is the extinction of fires (tasks) in an environment altered by a natural disaster. Finally, the experimental results are promising and show the effectiveness of the proposed methodology.

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Acknowledgment

We would like to thank vividly MS Abida Habiba FARDJALLAH for her help in improving this manuscript.

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Authors and Affiliations

  1. KASDI Merbah University, Ouargla, Algeria

    Farouq Zitouni

  2. Constantine 2, Abdelhamid MEHRI University, Constantine, Algeria

    Ramdane Maamri

Authors
  1. Farouq Zitouni
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  2. Ramdane Maamri
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Correspondence to Farouq Zitouni .

Editor information

Editors and Affiliations

  1. Carinthia University of Applied Sciences, Villach, Austria

    Michael E. Auer

  2. Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece

    Thrasyvoulos Tsiatsos

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Zitouni, F., Maamri, R. (2018). Cooperative Learning-Agents for Task Allocation Problem. In: Auer, M., Tsiatsos, T. (eds) Interactive Mobile Communication Technologies and Learning. IMCL 2017. Advances in Intelligent Systems and Computing, vol 725. Springer, Cham. https://doi.org/10.1007/978-3-319-75175-7_93

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  • DOI: https://doi.org/10.1007/978-3-319-75175-7_93

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-75174-0

  • Online ISBN: 978-3-319-75175-7

  • eBook Packages: EngineeringEngineering (R0)

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