Searching for "Where the Really Hard Problems Are." – sorted by Relevance.
-
Implementing and Testing Expressive Description Logics: a Preliminary Report
- Cheeseman, Bob Kanefsky, and William M. Taylor. Where the really hard problems are. In Proc. of the 12 th
- Add To MetaCart
-
Estimating the Hardness of Optimisation
- is the same. Even worse, the variance of hardness is largest in the transitional region, where the really hard
- Add To MetaCart
-
Optimizing through Co-Evolutionary Avalanches
- hill-climbing ability, which enables EO to perform well at phase transitions, "where the really hard
- Cited by 1 (0 self) – Add To MetaCart
-
Optimizing through Co-Evolutionary Avalanches
- at phase transitions, \where the really hard problems are" [11, 1]. 3 One popular hard optimization
- Add To MetaCart
-
Combining Local Search with Co-Evolution in a Remarkably Simple Way
- enables it to perform well at the phase transitions "where the really hard problems are" [CKT91, AI96
- Cited by 1 (0 self) – Add To MetaCart
-
Where the REALLY Hard Problems Are
- Kanefsky, and William M. Taylor. Where the really hard problems are. In J. Mylopoulos and R. Reiter
- Cited by 1 (0 self) – Add To MetaCart
-
A Shot in the Dark
- or determine that no solution is possible. This, in the words of some researchers, is “where the really hard
- Add To MetaCart
-
American Scientist
- of α. (An influential paper about this effect was aptly titled “Where the really hard problems are
- Cited by 1 (0 self) – Add To MetaCart
-
Computing science: Can’t get no satisfaction
- and William M. Taylor. Titled “Where the Really Hard Problems Are,” it reviewed evidence of phase transitions
- Cited by 5 (0 self) – Add To MetaCart
-
Extremal optimization: An evolutionary local-search algorithm
- from an ensemble with up to 10 4 variables, chosen from “Where the really hard problems are” [4
- Cited by 5 (0 self) – Add To MetaCart

