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GECCO
2007
Springer
151views Optimization» more  GECCO 2007»
15 years 9 months ago
Solving real-valued optimisation problems using cartesian genetic programming
Classical Evolutionary Programming (CEP) and Fast Evolutionary Programming (FEP) have been applied to realvalued function optimisation. Both of these techniques directly evolve th...
James Alfred Walker, Julian Francis Miller
GECCO
2005
Springer
151views Optimization» more  GECCO 2005»
15 years 8 months ago
Backward-chaining genetic programming
Tournament selection is the most frequently used form of selection in genetic programming (GP). Tournament selection chooses individuals uniformly at random from the population. A...
Riccardo Poli, William B. Langdon
98
Voted
CORR
2008
Springer
131views Education» more  CORR 2008»
15 years 3 months ago
Optimizing polynomials for floating-point implementation
The floating-point implementation of a function often reduces to a polynomial approximation on an interval. Remez algorithm provides the polynomial closest to the function, but th...
Florent de Dinechin, Christoph Quirin Lauter
GECCO
2007
Springer
119views Optimization» more  GECCO 2007»
15 years 9 months ago
Optimising the flow of experiments to a robot scientist with multi-objective evolutionary algorithms
A Robot Scientist is a physically implemented system that applies artificial intelligence to autonomously discover new knowledge through cycles of scientific experimentation. Ad...
Emma Byrne
GECCO
2008
Springer
120views Optimization» more  GECCO 2008»
15 years 4 months ago
A robust evolutionary framework for multi-objective optimization
Evolutionary multi-objective optimization (EMO) methodologies, suggested in the beginning of Nineties, focussed on the task of finding a set of well-converged and well-distribute...
Kalyanmoy Deb