Abstract
In Cultural Systems there are many ways to collect and distribute problem solving knowledge within social networks. Such mechanisms include games, auctions, and various voting mechanisms. Here, a new auction mechanism, Common Value Auctions, is presented. In this paper Common Value Auctions are used to distribute problem solving knowledge within a given model of social systems. These mechanisms are compared with the other distribution mechanisms in the solution of dynamic real-valued optimization problems. Specifically, their relative abilities to support the robustness and resilience of Cultural Systems in environments that vary in their dynamic complexity from static to chaotic are assessed. The Cultural Algorithms Toolkit (CAT) is used as a vehicle to generate real-valued dynamic problem landscapes of varying complexities. The results show that using the Common Value Auction in CAT4 has significant improvements over Weighted Voting methods (CAT2) in terms of both robustness and resilience across complexities that range from static to chaotic.
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