• DocumentCode
    3043361
  • Title

    Project planning and management using autonomous mobile agents, machine learning and negotiation protocols

  • Author

    Fordyce, Michael G. ; Tyler, Jon E M

  • Author_Institution
    Robert Gordon Univ., Aberdeen, UK
  • Volume
    2
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    610
  • Abstract
    Scheduling project activities is an iterative and time-consuming process. This paper describes an innovative technique which can be used to automate these processes. The techniques described have been demonstrated through the implementation of a prototype automatic scheduler for meetings. The software uses an incremental learning algorithm to determine user preferences. The preferences are applied to a dedicated negotiation protocol to shorten the cycle of negotiation and to produce a result acceptable to all the users. The prototype system utilises mobile object and autonomous agents with dedicated communication protocols. A test bed was developed to evaluate the performance of the system
  • Keywords
    learning (artificial intelligence); planning; project management; protocols; scheduling; software agents; time management; automatic meetings scheduler; autonomous agents; autonomous mobile agents; dedicated communication protocols; dedicated negotiation protocol; incremental learning algorithm; innovative technique; machine learning; mobile object; negotiation cycle shortening; negotiation protocols; project activities scheduling; project management; project planning; system performance; user preferences; Autonomous agents; Iterative algorithms; Mobile agents; Mobile communication; Project management; Protocols; Prototypes; Software algorithms; Software prototyping; System testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Management of Innovation and Technology, 2000. ICMIT 2000. Proceedings of the 2000 IEEE International Conference on
  • Print_ISBN
    0-7803-6652-2
  • Type

    conf

  • DOI
    10.1109/ICMIT.2000.916762
  • Filename
    916762