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Utilización Del Aprendizaje Inductivo En La Toma De Decisiones. Aplicación En Un Problema De Secuenciación /

Author

Listed:
  • Priore, P
  • De la Fuente, D.
  • Pino, R.
  • Puente, J

Abstract

El aprendizaje inductivo, que pertenece al campo de la inteligencia artificial, permite resolver un problema mediante el empleo de problemas resueltos en el pasado similares al planteado. En este artículo se describen las principales características del aprendizaje inductivo, así como las aplicaciones más comunes en las que se utiliza esta técnica. Asimismo, a modo de ejemplo, se presenta, de forma detallada, una aplicación en la que se emplea aprendizaje inductivo. En ésta, se resuelve un problema de secuenciación en un sistema de fabricación flexible (FMS, de Flexible Manufacturing System). En este tipo de sistemas, la forma habitual de secuenciar dinámicamente los trabajos es mediante el empleo de reglas de secuenciación. Sin embargo, el problema de este método es que el comportamiento de las reglas depende del estado del sistema de fabricación, y no existe una regla que supere a las demás en todos los posibles estados que puede presentar el mismo. Para resolver este inconveniente, se presenta una metodología que utiliza aprendizaje inductivo que permite usar, en cada momento, la regla de secuenciación más adecuada. / Inductive learning, which is part ofthe field of artificial intelligence, allows a problem to be sol ved by using the solutions to problems in the past that are similar to the problem at hand. This paper describes the hallmarks of inductive learning, and the most common applications when this technique is applied. Furthermore, and by way of example, an application involving inductive leaming is presented in detail. In the application in question, a scheduling problem in a flexible manufacturing system (FMS) is solved. A common method of dynamically scheduling jobs in FMSs is to employ dispatching rules. However, the problem associated with this method is that the performance of the rules depends on the state of the system, but there is no rule that is superior to all the others for all the possible states the system might be in. To achieve this, an approach is presented that uses inductive learning that allows the best dispatching rule to be applied for each given moment in time.

Suggested Citation

  • Priore, P & De la Fuente, D. & Pino, R. & Puente, J, 2004. "Utilización Del Aprendizaje Inductivo En La Toma De Decisiones. Aplicación En Un Problema De Secuenciación /," Investigaciones Europeas de Dirección y Economía de la Empresa (IEDEE), Academia Europea de Dirección y Economía de la Empresa (AEDEM), vol. 10(3), pages 17-36.
  • Handle: RePEc:idi:jiedee:v:10:y:2004:i:3:p:17-36
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