Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Handbook of Formal Languages
Simulating evolutionary algorithms with eco-grammar systems
IWINAC'05 Proceedings of the First international work-conference on the Interplay Between Natural and Artificial Computation conference on Artificial Intelligence and Knowledge Engineering Applications: a bioinspired approach - Volume Part II
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Evolutionary Algorithms (EAs), biological inspired searching techniques, represent a research domain where theoretical proofs are still missing. Due to the lack of theoretical foundations, an extensive experimental work developed many variations of the basic model. Remarkable tendencies such as variable control parameters or parallel populations try to overcome the stagnation observed at the end of evolutions. We tried to study from theoretical point of view the possibility of modelling parallel EAs using Eco-grammar systems. We expect that our research opens a new perspective over EAs behavior and our framework can bring theoretical results that will lead to new recommendations for EAs architectures as well as for specific details requested by practical problems.