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» Training Neural Networks with GA Hybrid Algorithms
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CEC
2007
IEEE
15 years 6 months ago
Topology management in unstructured P2P networks using neural networks
Abstract-- Resource discovery is an essential problem in peerto-peer networks since there is no centralized index in which to look for information about resources. In a pure P2P ne...
Annemari Auvinen, Teemu Keltanen, Mikko Vapa
GECCO
2006
Springer
208views Optimization» more  GECCO 2006»
15 years 5 months ago
Comparing evolutionary and temporal difference methods in a reinforcement learning domain
Both genetic algorithms (GAs) and temporal difference (TD) methods have proven effective at solving reinforcement learning (RL) problems. However, since few rigorous empirical com...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
NPL
1998
87views more  NPL 1998»
15 years 1 months ago
Constrained Learning in Neural Networks: Application to Stable Factorization of 2-D Polynomials
Adaptive artificial neural network techniques are introduced and applied to the factorization of 2-D second order polynomials. The proposed neural network is trained using a const...
Stavros J. Perantonis, Nikolaos Ampazis, Stavros V...
GECCO
2007
Springer
174views Optimization» more  GECCO 2007»
15 years 8 months ago
Heuristic speciation for evolving neural network ensemble
Speciation is an important concept in evolutionary computation. It refers to an enhancements of evolutionary algorithms to generate a set of diverse solutions. The concept is stud...
Shin Ando
ESANN
2000
15 years 3 months ago
A neural network approach to adaptive pattern analysis - the deformable feature map
Abstract. In this paper, we presen t an algorithm that provides adaptive plasticity in function approximation problems: the deformable (feature) map (DM) algorithm. The DM approach...
Axel Wismüller, Frank Vietze, Dominik R. Ders...