Human-based evolutionary computation: Difference between revisions

Revision as of 07:33, 21 October 2006

Revision as of 07:36, 21 October 2006

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Human-based selection is a simplest human-based evolutionary computation procedure. It is used heavily today by websites outsourcing collection and selection of the content to humans (user-contributed content). Viewed as evolutionary computation, their mechanism supports two operations: initialization (when a user adds a new item) and selection (when a user expresses preference among items). The website software aggregates the preferences to compute the fitness of items so that it can promote the fittest items and discard the worst ones. Several methods of human-based selection were analytically compared in (Kosorukoff, 2000; Gentry, 2005).

Because the concept seems too simple, most of the websites implementing the idea can't avoid the common pitfall: [[informationinformational cascadescascade]] in soliciting human preference. For example, [[digg]]-style implementations, pervasive on the web, heavily bias subsequent human evaluations by prior ones by showing how many votes the items alredy have. This makes the aggregated evaluation depend on a very small initial sample of rarely independent evaluations. This encourages many people to game the system that might add to digg's popularity but retract from the quality of the featured results.

===Human-based evolution strategy===