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GECCO
2005
Springer
153views Optimization» more  GECCO 2005»
14 years 28 days ago
Evolving neural network ensembles for control problems
In neuroevolution, a genetic algorithm is used to evolve a neural network to perform a particular task. The standard approach is to evolve a population over a number of generation...
David Pardoe, Michael S. Ryoo, Risto Miikkulainen
GECCO
2009
Springer
199views Optimization» more  GECCO 2009»
14 years 15 hour ago
Using behavioral exploration objectives to solve deceptive problems in neuro-evolution
Encouraging exploration, typically by preserving the diversity within the population, is one of the most common method to improve the behavior of evolutionary algorithms with dece...
Jean-Baptiste Mouret, Stéphane Doncieux
ICRA
2002
IEEE
161views Robotics» more  ICRA 2002»
14 years 10 days ago
A Method for Co-Evolving Morphology and Walking Pattern of Biped Humanoid Robot
— In this paper, we present a method for co-evolving structures and controller of biped walking robots. Currently, biped walking humanoid robots are designed manually on trial-an...
Ken Endo, Fuminori Yamasaki, Takashi Maeno, Hiroak...
SOFTCO
2004
Springer
14 years 22 days ago
Designing Neural Networks Using Gene Expression Programming
Abstract. An artificial neural network with all its elements is a rather complex structure, not easily constructed and/or trained to perform a particular task. Consequently, severa...
Cândida Ferreira
IJCNN
2006
IEEE
14 years 1 months ago
Generalization Improvement in Multi-Objective Learning
— Several heuristic methods have been suggested for improving the generalization capability in neural network learning, most of which are concerned with a single-objective (SO) l...
Lars Gräning, Yaochu Jin, Bernhard Sendhoff