Classifier fitness based on accuracy
Evolutionary Computation
Toward a theory of generalization and learning in XCS
IEEE Transactions on Evolutionary Computation
Learning Classifier Systems: Looking Back and Glimpsing Ahead
Learning Classifier Systems
MICAI '09 Proceedings of the 8th Mexican International Conference on Artificial Intelligence
A first assessment of the use of extended relational alphabets in accuracy classifier systems
Proceedings of the 12th annual conference on Genetic and evolutionary computation
| Hi-index | 0.00 |
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.