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EPIA
2007
Springer
13 years 11 months ago
Improving Evolutionary Algorithms with Scouting
The goal of an Evolutionary Algorithm(EA) is to find the optimal solution to a given problem by evolving a set of initial potential solutions. When the problem is multi-modal, an ...
Konstantinos Bousmalis, Gillian M. Hayes, Jeffrey ...
IJRR
2008
139views more  IJRR 2008»
13 years 5 months ago
Learning to Control in Operational Space
One of the most general frameworks for phrasing control problems for complex, redundant robots is operational space control. However, while this framework is of essential importan...
Jan Peters, Stefan Schaal
CVPR
2004
IEEE
14 years 7 months ago
Learning a Restricted Bayesian Network for Object Detection
Many classes of images have the characteristics of sparse structuring of statistical dependency and the presence of conditional independencies among various groups of variables. S...
Henry Schneiderman
GECCO
2003
Springer
129views Optimization» more  GECCO 2003»
13 years 10 months ago
Inherent Fault Tolerance in Evolved Sorting Networks
This poster paper summarizes our research on fault tolerance arising as a by-product of the evolutionary computation process. Past research has shown evidence of robustness emergin...
Rob Shepherd, James A. Foster
BMCBI
2010
163views more  BMCBI 2010»
13 years 5 months ago
Reduced representation of protein structure: implications on efficiency and scope of detection of structural similarity
Background: Computational comparison of two protein structures is the starting point of many methods that build on existing knowledge, such as structure modeling (including modeli...
Zong Hong Zhang, Hwee Kuan Lee, Ivana Mihalek