In evolutionary computation, a human-based genetic algorithm (HBGA) is a genetic algorithm that allows humans to contribute solution suggestions to the evolutionary process. For this purpose, a HBGA has human interfaces for initialization, mutation, and recombinant crossover. As well, it may have interfaces for selective evaluation. In short, a HBGA outsources the operations of a typical genetic algorithm to humans.
Read more about Human-based Genetic Algorithm: Evolutionary Genetic Systems and Human Agency, Differences From A Plain Genetic Algorithm, Functional Features, Applications
Famous quotes containing the word genetic:
“We cannot think of a legitimate argument why ... whites and blacks need be affected by the knowledge that an aggregate difference in measured intelligence is genetic instead of environmental.... Given a chance, each clan ... will encounter the world with confidence in its own worth and, most importantly, will be unconcerned about comparing its accomplishments line-by-line with those of any other clan. This is wise ethnocentricism.”
—Richard Herrnstein (1930–1994)