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Implementation of Real-Time Local Search Method for Distributed Constraint Optimization with Message Loss in Pub/Sub Communication

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Advances in Practical Applications of Agents, Multi-Agent Systems, and Digital Twins: The PAAMS Collection (PAAMS 2024)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 15157))

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Abstract

We develop an experimental environment to verify decentralized real-time optimization methods using publish/subscribe (pub/sub) communication with low QoS settings. Research on the distributed constraint optimization problem (DCOP) explores fundamental combinatorial optimization problems in multiagent systems. However, the implementation of solution methods using practical communication systems requires further investigation. Recent robot control platforms and frameworks for IoT devices employ pub/sub communication models for relatively simple communication. A previous study addressed this situation and investigated a variant of an anytime local solution method for DCOPs allowing for temporarily missing agents in the solution process. We experimentally investigate this approach by implementing it in an environment of small board computers with an ROS2 framework. We also describe/verify the methodology of our practical experiment.

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References

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Acknowledgments

This study was supported in part by the Telecommunications Advancement Foundation (2022 Research Grant) and JSPS KAKENHI Grant Number 22H03647.

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Correspondence to Toshihiro Matsui .

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Matsui, T. (2025). Implementation of Real-Time Local Search Method for Distributed Constraint Optimization with Message Loss in Pub/Sub Communication. In: Mathieu, P., De la Prieta, F. (eds) Advances in Practical Applications of Agents, Multi-Agent Systems, and Digital Twins: The PAAMS Collection. PAAMS 2024. Lecture Notes in Computer Science(), vol 15157. Springer, Cham. https://doi.org/10.1007/978-3-031-70415-4_31

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  • DOI: https://doi.org/10.1007/978-3-031-70415-4_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-70414-7

  • Online ISBN: 978-3-031-70415-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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