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
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