State of XCS Classifier System Research

XCS is a new kind of learning classifier system that differs from the traditional one primarily in its definition of classifier fitness and its relation to contemporary reinforcement learning. Advantages of XCS include improved performance and an ability to form accurate maximal generalizations. This paper reviews recent research on XCS with respect to representation, predictive modeling, internal state, noise, and underlying theory and technique. A notation for environmental regularities is introduced. 2 1 Introduction A classifier system is a learning system that seeks to gain reinforcement from its environment based on an evolving set of condition-action rules called classifiers. Via a Darwinian process, classifiers useful in gaining reinforcement are selected and propagate over those less useful, leading to increasing system performance. The classifier system idea is due to Holland (1986), who laid out a framework that included generalizability of classifier conditions, internal ..