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
Link To Document :
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