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GECCO
2007
Springer
158views Optimization» more  GECCO 2007»
15 years 6 months ago
A new evolutionary model for detecting multiple optima
Multimodal optimization problems consist in detecting all global and local optima of a problem. A new evolutionary approach to multimodal optimization called Roaming technique (RO...
Rodica Ioana Lung, D. Dumitrescu
GECCO
2007
Springer
153views Optimization» more  GECCO 2007»
15 years 6 months ago
Analyzing the effects of module encapsulation on search space bias
Modularity is thought to improve the evolvability of biological systems [18, 22]. Recent studies in the field of evolutionary computation show that the use of modularity improves...
Ozlem O. Garibay, Annie S. Wu
CIG
2006
IEEE
15 years 6 months ago
Temporal Difference Learning Versus Co-Evolution for Acquiring Othello Position Evaluation
Abstract— This paper compares the use of temporal difference learning (TDL) versus co-evolutionary learning (CEL) for acquiring position evaluation functions for the game of Othe...
Simon M. Lucas, Thomas Philip Runarsson
ISCC
2005
IEEE
15 years 5 months ago
Improving Survivability through Traffic Engineering in MPLS Networks
The volume of higher priority Internet applications is increasing as the Internet continues to evolve. Customers require Quality of Service (QoS) guarantees with not only guarante...
Mina Amin, Kin-Hon Ho, George Pavlou, Michael P. H...
GECCO
2005
Springer
141views Optimization» more  GECCO 2005»
15 years 5 months ago
Behavior of finite population variable length genetic algorithms under random selection
In this work we provide empirical evidence that shows how a variable-length genetic algorithm (GA) can naturally evolve shorter average size populations. This reduction in chromos...
Hal Stringer, Annie S. Wu