Interactive evolutionary computation: Difference between revisions

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'''Interactive evolutionary computation''' (IEC) is a subsetgeneral ofterm for methods of [[evolutionary computation]] that use human evaluation instead or in addition to computational fitness function (see [[evolutionary computation]], [[fitness landscape]]. Usually human evaluation is necessary when the form of fitness function is not known (for example, visual appeal or attractiveness) or the result of optimization should fit a particular user preference (for example, color set of the user interface).

==IEC design issues==

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The number of evaluations that IEC can receive from one human user is limited by [[user fatigue]] which was reported by many researchers as a major problem. In addition, human evaluations are slow and expensive as compared to fitness function computation. Hence, those IEC methods should be designed to converge using a small number of evaluations, which necessarily implies very small populations.

However IEC implementations that can concurrenlty accept evaluations from many users overcome the limitations described above. An example of this approach is an interactive media installation by [[Karl Sims]] that allows to accept preference from many visitors by using floor sensors to evolve attractive 3D animated forms. Some of these multi-user IEC implementations serve as collaboration tools, for example [[HBGA]].

==IEC implementations==

Examples of IEC methods include [[Interactive genetic algorithm]] and [[Human-based genetic algorithm]].

==See also==

[[Human-based genetic algorithm]], [[Interactive genetic algorithm]], [[Evolutionary art]]

==References==

*Takagi, H. (2001). Interactive Evolutionary Computation: Fushion of the Capacities of EC Optimization and Human Evaluation. ''Proceesings of the IEEE 89, 9,'' pp. 1275-1296

==External links==

*[http://www.genarts.com/galapagos/index.html Galapagos by Karl Sims]