Learn More
Learning Classifier Systems which build anticipations of the expected states following their actions are a focus of current research. This paper presents a mechanism by which to create learning classifier systems of this type, here using accuracybased fitness. In particular, we highlight the supervised learning nature of the anticipatory task and amend each(More)
In this paper, we study the use of anticipation mappings in learning classifier systems. At first, we enrich the eXtended Classifier System (XCS) with two types of anticipation mappings: one based on array of perceptrons array, one based on neural networks. We apply XCS with anticipation mappings (XCSAM) to several multistep problems taken from the(More)
  • 1