An anticipatory approach to improve XCSF

XCSF is a novel version of learning classifier systems (LCS) which extends the typical concept of LCS by introducing computable classifier prediction. In XCSF Classifier prediction is computed as a linear combination of classifier inputs and a weight vector associated to each classifier. Learning process takes place using a weight update mechanism. Initial results show that XCSF can be used to evolve accurate approximations of some functions. In this paper, we try to add an anticipatory component to XCSF improving its performance. Categories and Subject Descriptors I.2.6 [Learning]. General Terms Algorithms, Experimentation. Keywords Learning classifier system, Anticipatory classifier system, XCSF, Function approximation.

• Type: Conference
• Year: 2006
• Where: GECCO
• Authors: Amin Nikanjam, Adel Torkaman Rahmani
• Keywords: Classifier Prediction, Classifier System, GECCO 2006, Learning Classifier System, Optimization