Mixing expressiveness and efficiency in a manufacturing planner
Luis Castillo, Juan Fdez-Olivares, Antonio González · Journal of Experimental & Theoretical Artificial Intelligence · 2001
The application of artificial intelligence planning techniques to real world problems is a very difficult task which usually implies overcoming expressiveness and efficiency handicaps. Expressiveness in order to cope with the great amount of knowledge involved in these problems and also to obtain results directly, or almost directly, applicable in the field of study. Efficiency to achieve a good course through the potentially enormous search spaces and, therefore, a satisfactory response capability. This work describes MACHINE, a manufacturing planning architecture which is able to obtain sequential control programs for manufacturing systems, the steps given to overcome these expressiveness and efficiency handicaps and how it is able to solve some real size problems.