Cultural algorithms: modeling of how cultures learn to solve problems

Previous work on real-valued function optimization problems had shown that cultural learning emerged as the result of meta-level interaction or swarming of knowledge sources, "knowledge swarms" in the belief space. These meta-level swarms induced the swarming of individuals in the population space, "cultural swarms". The interaction of these knowledge source produced emergent phases of problem solving that reflected a branch and bound algorithmic process. We apply the approach to a real-world problem in engineering design. We observe the emergence of these same features in a completely different problem environment. We conclude by suggesting the emergent features are what give cultural systems their power to learn and adapt.