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Natural selection is the differential survival and reproduction of individuals due to differences in phenotype. It is a key mechanism of evolution, ...
In addition, selection mechanisms are also used to choose candidate solutions (individuals) for the next generation. The biological model is natural selection. Retaining the best individual(s) of one generation unchanged in the next generation is called elitism or elitist selection. It is a successful (slight) variant of the general process of ...
The earliest computational simulations of evolution using evolutionary algorithms and artificial life techniques were performed by Nils Aall Barricelli in 1953, with first results published in 1954. [6] Another pioneer in the 1950s was Alex Fraser, who published a series of papers on simulation of artificial selection. [7]
Tierra is a computer simulation developed by ecologist Thomas S. Ray in the early 1990s in which computer programs compete for time (central processing unit time) and space (access to main memory). In this context, the computer programs in Tierra are considered to be evolvable and can mutate , self-replicate and recombine .
PhET Interactive Simulations is part of the University of Colorado Boulder which is a member of the Association of American Universities. [10] The team changes over time and has about 16 members consisting of professors, post-doctoral students, researchers, education specialists, software engineers (sometimes contractors), educators, and administrative assistants. [11]
In natural selection, negative selection [1] or purifying selection is the selective removal of alleles that are deleterious. This can result in stabilising selection through the purging of deleterious genetic polymorphisms that arise through random mutations.
Fisher's fundamental theorem of natural selection is an idea about genetic variance [1] [2] in population genetics developed by the statistician and evolutionary biologist Ronald Fisher. The proper way of applying the abstract mathematics of the theorem to actual biology has been a matter of some debate, however, it is a true theorem.
The first and most common function to estimate fitness of a trait is linear ω =α +βz, which represents directional selection. [1] [10] The slope of the linear regression line (β) is the selection gradient, ω is the fitness of a trait value z, and α is the y-intercept of the fitness function.