• DocumentCode
    2324154
  • Title

    Learning monitoring strategies: a difficult genetic programming application

  • Author

    Atkin, Marc S. ; Cohen, Paul R.

  • Author_Institution
    Exp. Knowledge Syst. Lab., Massachusetts Univ., Amherst, MA, USA
  • fYear
    1994
  • fDate
    27-29 Jun 1994
  • Firstpage
    328
  • Abstract
    Finding optimal or at least good monitoring strategies is an important consideration when designing an agent. We have applied genetic programming to this task, with mixed results. Since the agent control language was kept purposefully general, the set of monitoring strategies constitutes only a small part of the overall space of possible behaviors. Because of this, it was often difficult for the genetic algorithm to evolve them, even though their performance was superior. These results raise questions as to how easy it will be for genetic programming to scale up as the areas it is applied to become more complex
  • Keywords
    genetic algorithms; learning (artificial intelligence); monitoring; optimisation; agent control language; genetic algorithm; genetic programming application; monitoring strategy learning; optimal strategies; possible behavior; Application software; Clocks; Computer science; Computerized monitoring; Condition monitoring; Costs; Genetic algorithms; Genetic programming; Knowledge based systems; Laboratories;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the First IEEE Conference on
  • Conference_Location
    Orlando, FL
  • Print_ISBN
    0-7803-1899-4
  • Type

    conf

  • DOI
    10.1109/ICEC.1994.349931
  • Filename
    349931