Learning Classifier Systems

This volume includes extended and revised versions of the papers presented at the 9th and 10th International Workshops on Learning Classi?er Systems (IWLCS 2006 and IWLCS 2007). Both workshops were held in association with theGeneticandEvolutionaryComputationConference(GECCO).IWLCS2006 was held on July 8th, 2006, in Seattle, USA, during GECCO 2006.IWLCS 2007 was held on July 8th, 2007, in London, UK, during GECCO 2007. The IWLCS is the annual meeting of researchers wishing to discuss recent developments in learning classi?er systems (LCS). At the last IWLCS, the LCS researchers commemorated the 10th anniversary of the workshop and ackno- edged the contribution of Stewart Wilson to the ?eld. Following his proposal of the XCS classi?er system in 1995, research on LCS was reactivated leading to signi?cant contributions and promising perspectives. The annual IWLCS wo- shops are the proof of this fruitful research. We include an invited paper from Stewart Wilson. We greatly appreciate his contribution to the volume. The contents of this book are as follows. First, Bacardit, Bernado ´-Mansilla and Butz review LCS research over the past ten years and point out new ch- lenges and open issues in the LCS ?eld. Next, papers investigating knowledge representations are presented. Lanzi et al. analyze the evolution of XCS with symbolic representations using a novel method that identi?es useful substr- tures and tracks the emergence of optimal solutions. Ioannides and Browne investigate the scaling of LCSs using ternary and symbolic representations.