• DocumentCode
    2453345
  • Title

    Learning Collaborative Behavior by Observation

  • Author

    Johnson, Cynthia L. ; Gonzalez, Avelino J.

  • Author_Institution
    Dept of Electr. Eng. & Comput. Sci., Univ. of Central Florida, Orlando, FL, USA
  • fYear
    2010
  • fDate
    12-14 Dec. 2010
  • Firstpage
    99
  • Lastpage
    104
  • Abstract
    This paper presents a multi-agent framework capable of learning teamwork by observation. The system combines proven single entity learning by observation techniques with a multi-agent system shown to exhibit effective teamwork. An effective simulated production team is observed. An off-line training algorithm uses the observed data to develop behavior maps for a Collaborative Context-based Reasoning framework. The Collaborative Context-based Reasoning framework provides generic base classes capable of recreating the behavior of the original agents using the behavior maps developed by the training algorithm. The resulting prototype effectively replaces the original team of agents and is capable of reproducing its behavior and generalizing the behavior to encompass similar situations.
  • Keywords
    inference mechanisms; learning (artificial intelligence); multi-agent systems; behavior maps; collaborative context-based reasoning framework; learning collaborative behavior; learning teamwork; multiagent framework; multiagent system; observation; offline training algorithm; single entity learning; Context; Prototypes; Robots; Teamwork; Training; Unified modeling language; Water resources; learning by observation; multi-agent learning; teamwork;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Applications (ICMLA), 2010 Ninth International Conference on
  • Conference_Location
    Washington, DC
  • Print_ISBN
    978-1-4244-9211-4
  • Type

    conf

  • DOI
    10.1109/ICMLA.2010.22
  • Filename
    5708819