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GECCO
2006
Springer
150views Optimization» more  GECCO 2006»
13 years 11 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»
13 years 11 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»
13 years 11 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
13 years 11 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
13 years 10 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 ...