• DocumentCode
    3291629
  • Title

    Pheromone-based ant colony clustering algorithm in multi-agent cooperation

  • Author

    Tang Xian-lun ; Li Ya-nan ; Fan Zheng ; Wang Guan-xiang ; Cai Lin-qing

  • Author_Institution
    Key Lab. of Network Control & Intell. Instrum., Chongqing Univ. of Posts & Telecommun., Chongqing, China
  • fYear
    2011
  • fDate
    15-17 April 2011
  • Firstpage
    3430
  • Lastpage
    3433
  • Abstract
    Cooperation is a key issue of multi-agent system (MAS), pursuit problem as a test platform of multi-agent system and learning algorithm is widely used for testing the performance of cooperation, learning method and communication of MAS. To reduce the large computation of current pursuit methods such as the shortest distance first and contract net protocol, a method of applying pheromone-based ant colony clustering algorithm in multi-agent pursuit problem is proposed. Experiment results show that the proposed method can speed up the pursuit process compared with other algorithms, when increasing the number of predators the proposed method shows its superiority on efficiency and can be applied in multi-agent cooperation effectively.
  • Keywords
    learning (artificial intelligence); multi-agent systems; optimisation; pattern clustering; contract net protocol; learning algorithm; multiagent cooperation; multiagent system; pheromone-based ant colony clustering algorithm; pursuit process; shortest distance first; Algorithm design and analysis; Automation; Clustering algorithms; Conferences; Contracts; Java; Multiagent systems; ant colony clustering; cooperation; multi-agent; pursuit;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electric Information and Control Engineering (ICEICE), 2011 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-8036-4
  • Type

    conf

  • DOI
    10.1109/ICEICE.2011.5778228
  • Filename
    5778228