TY - GEN
T1 - Inconsistent heuristics
AU - Zahavi, Uzi
AU - Felner, Ariel
AU - Schaeffer, Jonathan
AU - Sturtevant, Nathan
PY - 2007
Y1 - 2007
N2 - In the field of heuristic search it is well-known that improving the quality of an admissible heuristic can significantly decrease the search effort required to find an optimal solution. Existing literature often assumes that admissible heuristics are consistent, implying that consistency is a desirable attribute. To the contrary, this paper shows that an inconsistent heuristic can be preferable to a consistent heuristic. Theoretical and empirical results show that, in many cases, inconsistency can be used to achieve large performance improvements.
AB - In the field of heuristic search it is well-known that improving the quality of an admissible heuristic can significantly decrease the search effort required to find an optimal solution. Existing literature often assumes that admissible heuristics are consistent, implying that consistency is a desirable attribute. To the contrary, this paper shows that an inconsistent heuristic can be preferable to a consistent heuristic. Theoretical and empirical results show that, in many cases, inconsistency can be used to achieve large performance improvements.
UR - http://www.scopus.com/inward/record.url?scp=36348994827&partnerID=8YFLogxK
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AN - SCOPUS:36348994827
SN - 1577353234
SN - 9781577353232
T3 - Proceedings of the National Conference on Artificial Intelligence
SP - 1211
EP - 1216
BT - AAAI-07/IAAI-07 Proceedings
T2 - AAAI-07/IAAI-07 Proceedings: 22nd AAAI Conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence Conference
Y2 - 22 July 2007 through 26 July 2007
ER -