Sophisticated and distributed: The transportation domain

Exploring emergent functionality in a real-world application
  • K. Fischer
  • N. Kuhn
  • H. J. Müller
  • J. P. Müller
  • M. Pischel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 957)


In this paper, we present the MARS multi-agent system. MARS models a society of cooperating transportation companies. Emphasis is placed on how the functionality of the system as a whole — the solution of the global scheduling problem — emerges from local decision-making and problem-solving strategies, and on how variations of these strategies influence the performance of the system. We address three techniques of Distributed Artificial Intelligence (DAI) which are used for tackling the hard problems that occur in this domain, and which together give rise to the emergence of a solution to the global scheduling problem: (1) cooperation among the agents, (2) task decomposition and task allocation, and (3) decentralised planning. Finally, we briefly describe the implementation of the system and provide experimental results which show how different strategies for task decomposition and cooperation influence the behaviour of the system.


Schedule Problem Task Allocation Shipping Company Task Decomposition Transportation Order 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • K. Fischer
    • 1
  • N. Kuhn
    • 1
  • H. J. Müller
    • 1
  • J. P. Müller
    • 1
  • M. Pischel
    • 1
  1. 1.DFKISaarbrücken

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