Crynodeb
The intuitive idea that good solutions to small problems can be reassembled into good solutions to larger prob lems is widely familiar in many fields including evolutionary computation. This idea has motivated the buildingblock hypothesis and modelbuilding optimization methods that aim to identify and exploit problem structure automatically. Recently, a small number of works make use of such ideas by learning problem structure and using this information in a particular manner: these works use the results of a simple search process in primitive units to identify structural correlations (such as modularity) in the problem that are then used to redefine the variational operators of the search process. This process is applied recursively such that search operates at successively higher scales of organization, hence multiscale search. Here, we show for the first time that there is a simple class of (modular) problems that a multiscale search algorithm can solve in polynomial time that requires superpolynomial time for other methods. We discuss strengths and limitations of the multiscale search approach and note how it can be developed further.
Iaith wreiddiol  Saesneg 

Tudalennau (oi)  628642 
Nifer y tudalennau  15 
Cyfnodolyn  IEEE Transactions on Evolutionary Computation 
Cyfrol  18 
Rhif cyhoeddi  5 
Dyddiad arlein cynnar  13 Awst 2014 
Dynodwyr Gwrthrych Digidol (DOIs)  
Statws  Cyhoeddwyd  31 Hyd 2014 
Ôl bys
Gweld gwybodaeth am bynciau ymchwil 'Transforming Evolutionary Search into HigherLevel Evolutionary Search by Capturing Problem Structure'. Gyda’i gilydd, maen nhw’n ffurfio ôl bys unigryw.Proffiliau

Thomas Jansen
 Cyfadran Busnes a’r Gwyddorau Ffisegol, Cyfrifiadureg  Reader, Head of Department (Computer Science)
Unigolyn: Dysgu ac Ymchwil, Arall