Immigration is generally considered an option in genetic algorithms, but I have found immigration to be extremely useful in almost all situations where I use evolutionary optimization. The idea of ...

Evolutionary computation comprises a family of metaheuristic algorithms inspired by the principles of natural evolution – reproduction, mutation, recombination, and selection – which are utilised to ...

Constantly "re-rolling the dice", combining and selecting: "Evolutionary algorithms" mimic natural evolution in silico and lead to innovative solutions for complex problems. Constantly “re-rolling the ...

Researchers from 24 countries have analyzed the genomes of 809 individuals from 233 primate species, generating the most complete catalog of genomic information about our closest relatives to date.

This course will guide students on their own intellectual journey in evolutionary computation. Early lectures provide a jumping off point — an overview of genetic algorithms, evolutionary strategies, ...

Modern humans descended from not one, but at least two ancestral populations that drifted apart and later reconnected, long before modern humans spread across the globe. Using advanced analysis based ...

The growth and expansion of metropolitan areas has been evident over the past decade. Buildings are getting taller, and urban areas are getting larger. What if there was a way to predict this growth ...

MPN-BP transformation is driven by sequential mutations disrupting genomic stability, with TP53 mutations being strong predictors of progression. TP53 mutations confer a selective growth advantage, ...