Sciweavers

GECCO
2008
Springer
179views Optimization» more  GECCO 2008»
13 years 5 months ago
ASAGA: an adaptive surrogate-assisted genetic algorithm
Genetic algorithms (GAs) used in complex optimization domains usually need to perform a large number of fitness function evaluations in order to get near-optimal solutions. In rea...
Liang Shi, Khaled Rasheed
GECCO
2008
Springer
110views Optimization» more  GECCO 2008»
13 years 5 months ago
Evolving stable behavior in a spino-neuromuscular system model
This paper demonstrates the effectiveness of genetic algorithms in training stable behavior in a model of the spinoneuromuscular system (SNMS). In particular, we test the stabili...
Stanley Phillips Gotshall, Terry Soule
GECCO
2008
Springer
134views Optimization» more  GECCO 2008»
13 years 5 months ago
Branch predictor on-line evolutionary system
In this work a branch prediction system which utilizes evolutionary techniques is introduced. It allows the predictor to adapt to the executed code and thus to improve its perform...
Karel Slany
GECCO
2008
Springer
143views Optimization» more  GECCO 2008»
13 years 5 months ago
Genetic algorithms for mentor-assisted evaluation function optimization
In this paper we demonstrate how genetic algorithms can be used to reverse engineer an evaluation function’s parameters for computer chess. Our results show that using an approp...
Omid David-Tabibi, Moshe Koppel, Nathan S. Netanya...
GECCO
2008
Springer
131views Optimization» more  GECCO 2008»
13 years 5 months ago
Self-adaptive mutation in XCSF
Recent advances in XCS technology have shown that selfadaptive mutation can be highly useful to speed-up the evolutionary progress in XCS. Moreover, recent publications have shown...
Martin V. Butz, Patrick O. Stalph, Pier Luca Lanzi
GECCO
2008
Springer
129views Optimization» more  GECCO 2008»
13 years 5 months ago
Exploiting the path of least resistance in evolution
Hereditary Repulsion (HR) is a selection method coupled with a fitness constraint that substantially improves the performance and consistency of evolutionary algorithms. This als...
Gearoid Murphy, Conor Ryan
GECCO
2008
Springer
156views Optimization» more  GECCO 2008»
13 years 5 months ago
Computing minimum cuts by randomized search heuristics
We study the minimum s-t-cut problem in graphs with costs on the edges in the context of evolutionary algorithms. Minimum cut problems belong to the class of basic network optimiz...
Frank Neumann, Joachim Reichel, Martin Skutella
GECCO
2008
Springer
122views Optimization» more  GECCO 2008»
13 years 5 months ago
Evolving machine microprograms
The realization of a control unit can be done using a complex circuitry or microprogramming. The latter may be considered as an alternative method of implementation of machine ins...
Pedro A. Castillo Valdivieso, G. Fernández,...
GECCO
2008
Springer
165views Optimization» more  GECCO 2008»
13 years 5 months ago
Dual-population genetic algorithm for nonstationary optimization
In order to solve nonstationary optimization problems efficiently, evolutionary algorithms need sufficient diversity to adapt to environmental changes. The dual-population genetic...
Taejin Park, Ri Choe, Kwang Ryel Ryu
GECCO
2008
Springer
128views Optimization» more  GECCO 2008»
13 years 5 months ago
A tree-based GA representation for the portfolio optimization problem
Recently, a number of works have been done on how to use Genetic Algorithms to solve the Portfolio Optimization problem, which is an instance of the Resource Allocation problem cl...
Claus de Castro Aranha, Hitoshi Iba