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126
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CEC
2005
IEEE
15 years 10 months ago
A hybrid approach to parameter tuning in genetic algorithms
Abstract- Choosing the best parameter setting is a wellknown important and challenging task in Evolutionary Algorithms (EAs). As one of the earliest parameter tuning techniques, th...
Bo Yuan, Marcus Gallagher
GECCO
2005
Springer
117views Optimization» more  GECCO 2005»
15 years 10 months ago
Directional self-learning of genetic algorithm
In order to overcome the low convergence speed and prematurity of classical genetic algorithm, an improved method named directional self-learning of genetic algorithm (DSLGA) is p...
Lin Cong, Yuheng Sha, Licheng Jiao, Fang Liu
GECCO
2004
Springer
108views Optimization» more  GECCO 2004»
15 years 10 months ago
Simple Population Replacement Strategies for a Steady-State Multi-objective Evolutionary Algorithm
This paper explores some simple evolutionary strategies for an elitist, steady-state Pareto-based multi-objective evolutionary algorithm. The experimental framework is based on the...
Christine L. Mumford
148
Voted
ICTAI
1993
IEEE
15 years 8 months ago
Robust Feature Selection Algorithms
Selecting a set of features which is optimal for a given task is a problem which plays an important role in a wide variety of contexts including pattern recognition, adaptive cont...
Haleh Vafaie, Kenneth DeJong
138
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CG
2008
Springer
15 years 6 months ago
A Parallel Monte-Carlo Tree Search Algorithm
Monte-Carlo tree search is a powerful paradigm for the game of Go. We present a parallel Master-Slave algorithm for Monte-Carlo tree search. We experimented the algorithm on a netw...
Tristan Cazenave, Nicolas Jouandeau