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» Entropy-Driven Parameter Control for Evolutionary Algorithms
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CEC
2009
IEEE
14 years 2 months ago
Dynamic optimization using Self-Adaptive Differential Evolution
Abstract— In this paper we investigate a Self-Adaptive Differential Evolution algorithm (jDE) where F and CR control parameters are self-adapted and a multi-population method wit...
Janez Brest, Ales Zamuda, Borko Boskovic, Mirjam S...
GECCO
2007
Springer
256views Optimization» more  GECCO 2007»
14 years 1 months ago
A particle swarm optimization approach for estimating parameter confidence regions
Point estimates of the parameters in real world models convey valuable information about the actual system. However, parameter comparisons and/or statistical inference requires de...
Praveen Koduru, Stephen Welch, Sanjoy Das
IWINAC
2007
Springer
14 years 1 months ago
Evolving Robot Behaviour at Micro (Molecular) and Macro (Molar) Action Level
We investigate how it is possible to shape robot behaviour adopting a molecular or molar point of view. These two ways to approach the issue are inspired by Learning Psychology, wh...
Michela Ponticorvo, Orazio Miglino
GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
14 years 1 months ago
An experimental analysis of evolution strategies and particle swarm optimisers using design of experiments
The success of evolutionary algorithms (EAs) depends crucially on finding suitable parameter settings. Doing this by hand is a very time consuming job without the guarantee to ...
Oliver Kramer, Bartek Gloger, Andreas Goebels
GECCO
2009
Springer
130views Optimization» more  GECCO 2009»
14 years 2 months ago
The impact of jointly evolving robot morphology and control on adaptation rate
Embodied cognition emphasizes that intelligent behavior results from the coupled dynamics between an agent’s body, brain and environment. In response to this, several projects h...
Josh C. Bongard