Searching for Macro Operators with Automatically Generated Heuristics

Authors:
István T. Hernádvölgyi
Affiliations:
-
Venue:
AI '01 Proceedings of the 14th Biennial Conference of the Canadian Society on Computational Studies of Intelligence: Advances in Artificial Intelligence
Year:
2001

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Abstract

Macro search is used to derive solutions quickly for large search spaces at the expense of optimality. We present a novel way of building macro tables. Our contribution is twofold: (1) for the first time, we use automatically generated heuristics to find optimal macros, (2) due to the speed-up achieved by (1), we merge consecutive subgoals to reduce the solution lengths. We use the Rubik's Cube to demonstrate our techniques. For this puzzle, a 44% improvement of the average solution length was achieved over macro tables built with previous techniques.