Abstract. Evolutionary algorithms such as genetic programming and grammatical evolution have been used for simultaneously optimizing network architecture, variable selection, and w...
Stephen D. Turner, Marylyn D. Ritchie, William S. ...
One of the open questions in evolutionary computation is how an arms race may be initiated between coevolving entities such that the entities acquire new behaviors and increase in ...
In this paper, we develop techniques based on evolvability statistics of the fitness landscape surrounding sampled solutions. Averaging the measures over a sample of equal fitness...
Tom Smith, Phil Husbands, Paul J. Layzell, Michael...
We study the response of populations of digital organisms that adapt to a time-varying (periodic) fitness landscape of two oscillating peaks. We corroborate in general predictions ...
The best evolutionary approach can be a difficult problem. In this work we have investigated two evolutionary representations to evolve non-photorealistic renderings: a variable-le...
The performance of Evolutionary Programming (EP) is affected by many factors (e.g. mutation operators and selection strategies). Although the conventional approach with Gaussian mu...
In multimodal function optimization, niching techniques create diversification within the population, thus encouraging heterogeneous convergence. The key to the effective diversif...
The traditional GA theory is pillared on the Building Block Hypothesis (BBH) which states that Genetic Algorithms (GAs) work by discovering, emphasizing and recombining low order ...