Coordinated Collaboration of Multiagent Systems Based on Genetic Algorithms

  • Keon Myung Lee
  • Jee-Hyong Lee
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2891)


This paper is concerned with coordinated collaboration of multiagent systems in which there exist multiple agents which have their own set of skills to perform some tasks, multiple external resources which can be either used exclusively by an agent or shared by the specified number of agents at a time, and a set of tasks which consist of a collection of subtasks each of which can be carried out by an agent. Even though a subtask can be carried out by several agents, its processing cost may be different depending on which agent performs it. To process tasks, some coordination work is required such as allocating their constituent subtasks among competent agents and scheduling the allocated subtasks to determine their processing order at each agent. This paper proposes a genetic algorithm-based method to coordinate the agents to process tasks in the considered multiagent environments. It also presents some experiment results for the proposed method and discusses the pros and cons of the proposed method.


Genetic Algorithm Candidate Solution Multiagent System Task Schedule Task Allocation 
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 2003

Authors and Affiliations

  • Keon Myung Lee
    • 1
  • Jee-Hyong Lee
    • 2
  1. 1.School of Electric and Computer EngineeringChungbuk National University, and Advanced Information Technology Research Center(AITrc)Korea
  2. 2.School of Information and Communication EngineeringSungKyunKwan UniversityKorea

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