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Genetic programming (GP) is an evolutionary algorithm, an artificial intelligence technique mimicking natural evolution, which operates on a population of programs. It applies the genetic operators selection according to a predefined fitness measure , mutation and crossover .
Genetic programming (GP) is a related technique popularized by John Koza in which computer programs, rather than function parameters, are optimized. Genetic programming often uses tree-based internal data structures to represent the computer programs for adaptation instead of the list structures typical of genetic
From genetic algorithms it inherited the linear chromosomes of fixed length; and from genetic programming it inherited the expressive parse trees of varied sizes and shapes. In gene expression programming the linear chromosomes work as the genotype and the parse trees as the phenotype, creating a genotype/phenotype system.
Behavioral epigenetics is the field of study examining the role of epigenetics in shaping animal and human behavior. [1] It seeks to explain how nurture shapes nature, [2] where nature refers to biological heredity [3] and nurture refers to virtually everything that occurs during the life-span (e.g., social-experience, diet and nutrition, and exposure to toxins). [4]
This approach to genetic association studies is largely atheoretical, and typically not guided by a particular biological hypothesis regarding the phenotype. [33] Genetic association findings for behavioural traits and psychiatric disorders have been found to be highly polygenic (involving many small genetic effects).
Cognitive genomics (or neurative genomics) is the sub-field of genomics pertaining to cognitive function in which the genes and non-coding sequences of an organism's genome related to the health and activity of the brain are studied.
Fetal programming, also known as prenatal programming, is the theory that environmental cues experienced during fetal development play a seminal role in determining health trajectories across the lifespan. Three main forms of programming that occur due to changes in the maternal environment are:
Evolutionary programming is an evolutionary algorithm, where a share of new population is created by mutation of previous population without crossover. [ 1 ] [ 2 ] Evolutionary programming differs from evolution strategy ES( μ + λ {\displaystyle \mu +\lambda } ) in one detail. [ 1 ]