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GECCO
2005
Springer
120views Optimization» more  GECCO 2005»
14 years 29 days ago
Exploiting gradient information in numerical multi--objective evolutionary optimization
Various multi–objective evolutionary algorithms (MOEAs) have obtained promising results on various numerical multi– objective optimization problems. The combination with gradi...
Peter A. N. Bosman, Edwin D. de Jong
EH
2003
IEEE
100views Hardware» more  EH 2003»
14 years 22 days ago
Learning for Evolutionary Design
This paper describes a technique for evolving similar solutions to similar configuration design problems. Using the configuration design of combination logic circuits as a testb...
Sushil J. Louis
EVOW
2006
Springer
13 years 11 months ago
A Memetic Algorithm with Bucket Elimination for the Still Life Problem
Abstract. Bucket elimination (BE) is an exact technique based on variable elimination, commonly used for solving constraint satisfaction problems. We consider the hybridization of ...
José E. Gallardo, Carlos Cotta, Antonio J. ...
CORR
2010
Springer
152views Education» more  CORR 2010»
13 years 7 months ago
Neuroevolutionary optimization
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
Eva Volná
GECCO
2006
Springer
133views Optimization» more  GECCO 2006»
13 years 11 months ago
A general coarse-graining framework for studying simultaneous inter-population constraints induced by evolutionary operations
The use of genotypic populations is necessary for adaptation in Evolutionary Algorithms. We use a technique called form-invariant commutation to study the immediate effect of evol...
Keki M. Burjorjee, Jordan B. Pollack