an approach to analyze the evolution of symbolic conditions in learning classifier systems
In this paper, we introduce an approach for the identification of building blocks in symbolic expressions and apply it to analyze the emergence of building blocks in XCS with symbolic representation. The objective is to extract from a sequence of evolving populations a set of recurrent patterns which identifies pieces of the problem solution, so to track the emergence of the optimal solution. This permits the introduction of better measures of performance which might be useful in diagnosing problems and adapting algorithms.
symbolic conditions xcs representation lcs