A Self-Adaptive Approach to Representation Shifts in Cultural Algorithms

The paper describes how a formal model of selfadaptation [Angeline, 1995] can be expressed in terms of Cultural Algorithms. A particular form of self-adaptation concerns the shifting of the representational bias used to described the set of learned beliefs within the Cultural Algorthms. A version of Cultural Algorithms with the ability to shift its representational bias was used to solve the Royal Road problem suggested by Holland. The results of the experiments indicate that representational self-adaptations such as this can produce significant performance improvements over systems without such capabilities for problems whose performance function is inherently hierarchical, as is the case in the Royal Road function.