Reorganization of agent networks with reinforcement learning based on communication delay

Kazuki Urakawa, Toshiharu Sugawara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

We propose the team formation method for task allocations in agent networks by reinforcement learning based on communication delay and by reorganization of agent networks. A task in a distributed environment like an Internet application, such as grid computing and service-oriented computing, is usually achieved by doing a number of subtasks. These subtasks are constructed on demand in a bottom-up manner and must be done with appropriate agents that have capabilities and computational resources required in each subtask. Therefore, the efficient and effective allocation of tasks to appropriate agents is a key issue in this kind of system. In our model, this allocation problem is formulated as the team formation of agents in the task-oriented domain. From this perspective, a number of studies were conducted in which learning and reorganization were incorporated. The aim of this paper is to extend the conventional method from two viewpoints. First, our proposed method uses only information available locally for learning, so as to make this method applicable to real systems. Second, we introduce the elimination of links as well as the generation of links in the agent network to improve learning efficiency. We experimentally show that this extension can considerably improve the efficiency of team formation compared with the conventional method. We also show that it can make the agent network adaptive to environmental changes.

Original languageEnglish
Title of host publicationProceedings - 2012 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2012
Pages324-331
Number of pages8
DOIs
Publication statusPublished - 2012 Dec 1
Event2012 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2012 - Macau, China
Duration: 2012 Dec 42012 Dec 7

Publication series

NameProceedings - 2012 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2012
Volume2

Conference

Conference2012 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2012
CountryChina
CityMacau
Period12/12/412/12/7

Keywords

  • Distributed cooperative
  • Multi-agent reinforcement learning
  • Reorganization
  • Team formation

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

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  • Cite this

    Urakawa, K., & Sugawara, T. (2012). Reorganization of agent networks with reinforcement learning based on communication delay. In Proceedings - 2012 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2012 (pp. 324-331). [6511589] (Proceedings - 2012 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2012; Vol. 2). https://doi.org/10.1109/WI-IAT.2012.105