Inter-organizational networks as patterns for self-organizing multiagent systems

  • Authors:
  • Tore Knabe;Michael Schillo;Klaus Fischer

  • Affiliations:
  • German Research Center for Artificial Intelligence (DFKI), Saarbrücken, Germany;German Research Center for Artificial Intelligence (DFKI), Saarbrücken, Germany;German Research Center for Artificial Intelligence (DFKI), Saarbrücken, Germany

  • Venue:
  • AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
  • Year:
  • 2003

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Abstract

Market-based approaches for task-assignment multiagent systems consist of customer agents with jobs to assign, and provider agents that have the resources to perform these jobs. Jobs can be complex in the sense that they require the collaboration of several provider agents. We present a set of sociological forms of inter-organizational networks that have the potential to increase performance through the structure they impose on collaboration.This gain of structure is especially valuable in settings where communication is limited, which is an appropriate assumption in large-scale applications. We empirically evaluate these organizational forms according to the amount of communication required and the rate of failed task-assignments, and compare them to a system without organizational forms. Furthermore,we investigate the effect of letting agents choose at runtime in which kind of organizational form to engage and which other agents to choose for this collaboration.Our evaluation shows that the proposed organizational forms and mechanisms for self-organization have the ability to improve the efficiency of a market-based multiagent system.