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GECCO
2006
Springer
150views Optimization» more  GECCO 2006»
15 years 1 months ago
Nonlinear parametric regression in genetic programming
Genetic programming has been considered a promising approach for function approximation since it is possible to optimize both the functional form and the coefficients. However, it...
Yung-Keun Kwon, Sung-Soon Choi, Byung Ro Moon
GECCO
2006
Springer
206views Optimization» more  GECCO 2006»
15 years 1 months ago
A dynamically constrained genetic algorithm for hardware-software partitioning
In this article, we describe the application of an enhanced genetic algorithm to the problem of hardware-software codesign. Starting from a source code written in a high-level lan...
Pierre-André Mudry, Guillaume Zufferey, Gia...
GECCO
2006
Springer
164views Optimization» more  GECCO 2006»
15 years 1 months ago
A new generation alternation model for differential evolution
We present a modified version of Differential Evolution (DE) for locating the global minimum at a higher convergence velocity. The proposed model differs from conventional DE by a...
Nasimul Noman, Hitoshi Iba
ECAL
1995
Springer
15 years 1 months ago
Evolving Artificial Neural Networks that Develop in Time
Although recently there has been an increasing interest in studing genetically-based development using Artificial Life models, the mapping of the genetic information into the phen...
Stefano Nolfi, Domenico Parisi
ATAL
2008
Springer
14 years 11 months ago
Multi-robot Markov random fields
We propose Markov random fields (MRFs) as a probabilistic mathematical model for unifying approaches to multi-robot coordination or, more specifically, distributed action selectio...
Jesse Butterfield, Odest Chadwicke Jenkins, Brian ...