Support vector machines for computing action mappings in learning classifier systems

XCS with computed action, briefly XCSCA, is a recent extension of XCS to tackle problems involving a large number of discrete actions. In XCSCA the classifier action is computed with a parameterized function learned in a supervised fashion. In this paper, we introduce XCSCAsvm that extends XCSCA using support vector machines to compute classifier action. We compared XCSCAsvm and XCSCA on the learning of several binary functions. The experimental results show that XCSCAsvm reaches the optimal performance faster than XCSCA.