Titlebook: Artificial Evolution; 7th International Co El-Ghazali Talbi,Pierre Liardet,Marc Schoenauer Conference proceedings 2006 Springer-Verlag Berl

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https://doi.org/10.1007/978-3-642-82961-1of strong bonds, which we term dynamically bonding dissipative particle dynamics (DDPD). Then we use a chemical genetic algorithm (CGA) to optimize the model’s parameters to achieve a limited form of ligation of trimers—a proof of principle for the evolutionary design of self-assembling chemical systems.

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Santa Fe Trail Hazardsw genotype representations as found in works on grammar-based automatic programming, such as Grammatical Evolution, and Bayesian Automatic Programming. We extend a work by Langdon et al. by measuring the effort to solve SFT by random search with different time steps limits and a reduced but semantically equivalent function set.

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A Critical View of the Evolutionary Design of Self-assembling Systemsnd we discuss the difficulties encountered while applying EAs to these test cases. We also suggest some promising lines of work that could possibly help overcome current limitations in the evolutionary design of self-assembling systems.

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Evolutionary Design of a DDPD Model of Ligationof strong bonds, which we term dynamically bonding dissipative particle dynamics (DDPD). Then we use a chemical genetic algorithm (CGA) to optimize the model’s parameters to achieve a limited form of ligation of trimers—a proof of principle for the evolutionary design of self-assembling chemical systems.

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