Diversity as a Necessity for Sustainability in Cultural Systems: Collective Problem-Solving in Cultural Algorithms

Abstract

Cultural Algorithms have led to the development of many ways to distribute information within social networks. These mechanisms act by helping the system make decisions about how information is distributed through a population network, and thus are called distribution or decision mechanisms. Many distribution mechanisms have been developed using techniques from auction theory, game theory and various forms of voting construct. In this paper a new extension of a system called Subcultures is described. Previous forms of the Subcultures system involved allowing Knowledge Sources within the Belief Space to choose what network was used for their distribution in the Population Space based on the complexity of the problem at hand. Here the Subcultures system is extended to allow the selection of distribution mechanisms along with the network. The new Subcultured distribution mechanism is compared with the results of each individual distribution mechanism without a subculture, when applied to a series of dynamic complex optimization problems of varying complexities. The results suggest that relatively simple mechanism such as Weighted Majority Vote and First Price Auction are sufficient for environments that exhibit low entropic levels of change such as in linear environments. For non-linearly changing environments, English Auctions and Sub-Cultures are most of effective. For the most chaotic environments, the sub-cultured approach was the most effective of the two. What these results suggest that while voting approaches work well in predictably changing environments, cultural diversity is a necessity for sustainability in an environment that is changing nonlinearly. This information can be used by a human technician in the adjustment of the Cultural Algorithms during its operation over an extended period of time as the complexity of the environment changes.