Macro-operators is a problem solving technique in the field of artificial intelligence. The application of this technique depends on the generation of macro-operators. This research investigated macro-operators generation in the 15-puzzle. A method named "Iterative-Deepening Depth-First Search" and the relevant analysis were presented. A program using this method was developed in LISP. It was concluded that the performance of iterative-deepening depth-first search is much better than that of the ordinary exhaustive search methods. It was recommended that research be continued in searching for optimal macro-operators and improving the generation method.Ball State UniversityMuncie, IN 47306
| Identifer | oai:union.ndltd.org:BSU/oai:cardinalscholar.bsu.edu:handle/183454 |
| Date | 03 June 2011 |
| Creators | Li, Zhu |
| Contributors | Tzeng, Chun-Hung |
| Source Sets | Ball State University |
| Detected Language | English |
| Format | iv, 68 leaves : ill. ; 28 cm. |
| Source | Virtual Press |
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