Human-based evolutionary computation
Human-based evolutionary computation (HBEC) is a set of evolutionary computation techniques that rely on human innovation. Human-based evolutionary computation techniques can be classified into three more specific classes analogous to ones in evolutionary computation. There are three basic types of innovation: initialization, mutation, and recombination. Here is a table illustrating which type of human innovation are supported in different classes of HBEC:
| Initialization | Mutation | Recombination | |
| Human-based selection | X | ||
|---|---|---|---|
| Human-based evolution strategy | X | X | |
| Human-based genetic algorithm | X | X | X |
All these three classes also have to implement selection, performed either by humans or by computers.
Examples
In this context and maybe generally, the Wikipedia software is the best illustration of a working human-based evolution strategy. The initialization operator here is a page creation. The mutation operator is an incremental page edit. The selection operator is less salient. It is provided by the revision history and the ability to select among all previous revisions via revert operation. If the page is vandalised and no longer a good fit to its title, a reader can easily go to the revision history and select one of the previos revisions that fits best (hopefully, the previous one). This selection feature is crucial to the success of the Wikipedia.
An interesting fact is that the original wiki software was created in 1995, but it took at least another six years for large wiki-based collaborative projects to appear. Why did it take so long? One explanation is that the original wiki software was lacking selection operation and hence it couldn't effectively support content evolution. The addition of revision history and rise of large wiki-supported communities coincide in time. From evolutionary computation point of view this is not surprising: without selection operation the content would undergo an aimless genetic drift and would unlikely to be useful to anyone. That is what many people expect from Wikipedia at the very beginning. However, with selection operation, utility of the content have a tendency to improve over time as beneficial changes accumulate. This is what actually happens on a large scale in Wikipedia.
References
- Kosorukoff, A. (2000) Social classification structures. Optimal decision making in an organization, Genetic and Evolutionary Computation Conference, GECCO-2000, Late breaking papers, 175--178 online
- Kosorukoff, A. (2000) Human-based genetic algorithm online
- Cunningham, Ward and Leuf, Bo (2001): The Wiki Way. Quick Collaboration on the Web. Addison-Wesley, ISBN 0-201-71499-X.
- Kosorukoff, A (2001), Human-based Genetic Algorithm. IEEE Transactions on Systems, Man, and Cybernetics, SMC-2001, 3464-3469