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In computer science, a technique when an algorithm or computational process employs humans and relies on human abilities to perform its function, e.g. to solve a certain computational problem or a set of problems. This approach explores differences in abilities and alternative costs between humans and computer agents to achieve symbiotic human-computer interaction.
In traditional computation, a human presents a computer with a problem and later receives the result of computation, a solution. In human-based computation, the roles are reversed: computer asks a person or often many people to solve a problem, collects and integrates their solutions. Precursors of this idea are interactive programs requesting input from a user, e.g. asking a confirmation to delete a file. However, this concept in its explicit form appeared at the intersection of computer graphics and evolutionary computation. [Sims 91] used human visual perception and esthetic ability to implement evaluation function in evolutionary programming application and evolve pieces of graphic art this way. The crucial difference here is agency: Sim's program was no longer an agent of its user, but rather a coordinator of many human evaluators who became agents of the program. Human-based genetic algorithm is a logical extension of this approach where human also can contribute their innovative solutions into the process and thus have more control over the functions they are performing.
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