Human-based computation: Difference between revisions

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In computer science, a technique when an algorithm or computational process 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. This approach originated due to the intersection of computer graphics and evolutionary computation by [[Karl Sims]], who used human visual perception and esthetic ability to implement evaluation function in evolutionary programming application.

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. Precursor of this ides, for example, is an error message from a compiler that can be viewed as asking the programmer to fix an error. However, this approach in its explicit form appeared at the intersection of computer graphics and evolutionary computation, pioneered by [[Karl Sims]], who used human visual perception and esthetic ability to implement evaluation function in evolutionary programming application and evolve pieces of graphic art this way. Human-based genetic algorithm is a logical extension of this approach where human also can contribute their innovative solutions.

The following table from [Kosorukoff 00] uses the evolutionary computation model to describe four classes of computation, three of which rely on humans in some role. The classification is in terms of the roles (innovation or selection) performed in each case by humans and computational processes.