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CEC
2003
IEEE
15 years 3 months ago
Comparing neural networks and Kriging for fitness approximation in evolutionary optimization
Neural networks and the Kriging method are compared for constructing £tness approximation models in evolutionary optimization algorithms. The two models are applied in an identica...
Lars Willmes, Thomas Bäck, Yaochu Jin, Bernha...
93
Voted
GECCO
2005
Springer
220views Optimization» more  GECCO 2005»
15 years 3 months ago
Scale invariant pareto optimality: a meta--formalism for characterizing and modeling cooperativity in evolutionary systems
This article describes a mathematical framework for characterizing cooperativity in complex systems subject to evolutionary pressures. This framework uses three foundational compo...
Mark Fleischer
ESANN
2004
14 years 11 months ago
High-accuracy value-function approximation with neural networks applied to the acrobot
Several reinforcement-learning techniques have already been applied to the Acrobot control problem, using linear function approximators to estimate the value function. In this pape...
Rémi Coulom
EUROCAST
2007
Springer
132views Hardware» more  EUROCAST 2007»
15 years 1 months ago
Using Omnidirectional BTS and Different Evolutionary Approaches to Solve the RND Problem
RND (Radio Network Design) is an important problem in mobile telecommunications (for example in mobile/cellular telephony), being also relevant in the rising area of sensor network...
Miguel A. Vega-Rodríguez, Juan Antonio G&oa...
70
Voted
ICTAI
2009
IEEE
15 years 4 months ago
Probabilistic Neural Logic Network Learning: Taking Cues from Neuro-Cognitive Processes
This paper describes an attempt to devise a knowledge discovery model that is inspired from the two theoretical frameworks of selectionism and constructivism in human cognitive le...
Henry Wai Kit Chia, Chew Lim Tan, Sam Yuan Sung