Human-based genetic algorithm
Open-knowledge reference entry
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.
Evolutionary genetic systems and human agency
Among evolutionary genetic systems, HBGA is the computer-based analogue of genetic engineering (Allan, 2005).
This table compares systems on lines of human agency:
One obvious pattern in the table is the division between organic (top) and computer systems (bottom).
Another is the vertical symmetry between autonomous systems (top and bottom) and human-interactive systems (middle).
Looking to the right, the selector is the agent that decides fitness in the system.
It determines which variations will reproduce and contribute to the next generation.
In natural populations, and in genetic algorithms, these decisions are automatic; whereas in typical HBGA systems, they are made by people.
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This entry incorporates text from “Human-based genetic algorithm” on English Wikipedia. Contributors are listed in the page history. Text is available under the Creative Commons Attribution-ShareAlike 4.0 License. Selected authority identifiers and statements are retrieved from Wikidata under CC0; their references and qualifiers remain part of the verification path.