Applications
- Evolutionary knowledge management, integration of knowledge from different sources.
- Social organization, collective decision-making, and e-governance.
- Traditional areas of application of interactive genetic algorithms: computer art, user-centered design, etc.
- Collaborative problem solving using natural language as a representation.
The HBGA methodology was derived in 1999-2000 from analysis of the Free Knowledge Exchange project that was launched in the summer of 1998, in Russia (Kosorukoff, 1999). Human innovation and evaluation were used in support of collaborative problem solving. Users were also free to choose the next genetic operation to perform. Currently, several other projects implement the same model, the most popular being Yahoo! Answers, launched in December 2005.
Recent research suggests that human-based innovation operators are advantageous not only where it is hard to design an efficient computational mutation and/or crossover (e.g. when evolving solutions in natural language), but also in the case where good computational innovation operators are readily available, e.g. when evolving an abstract picture or colors (Cheng and Kosorukoff, 2004). In the latter case, human and computational innovation can complement each other, producing cooperative results and improving general user experience by ensuring that spontaneous creativity of users will not be lost.
Read more about this topic: Human-based Genetic Algorithm