Cooperation in the context of sustainable search

Many current evolutionary algorithms suffer from a tendency to prematurely lose their capability to incorporate new genetic material, resulting in a stagnation in suboptimal points. To successfully apply these methods on increasingly complex problems, the ability to generate useful variations leading to continuous improvements is vital. Nevertheless, there is a major difficulty in finding computational extensions to the evolutionary paradigm that ensures a continuous emergence of new qualitative solutions, as the essence of the Darwinian paradigm - the natural selection - acts as a stabilizing force, keeping the population into an evolutionary equilibria.