Learning Classifier Systems: 10th International Workshop, IWLCS 2006, Seattle, MA, USA, July 8, 2006, and 11th International Workshop, IWLCS 2007, London, UK, July 8, 2007, Revised Selected Papers - Lecture Notes in Computer Science 2008 edition

Marc Notes: ... the 9th and 10th International Workshops on Learning Classifier Systems (IWLCS 2006 and IWLCS 2007).--Pref.; Includes bibliographical references and index. Table of Contents: Introduction -- Learning Classifier Systems: Looking Back and Glimpsing Ahead / Jaume Bacardit, Ester Bernado-Mansilla, Martin V. Butz -- Knowledge Representations -- Analysis of Population Evolution in Classifier Systems Using Symbolic Representations / Pier Luca Lanzi, Stefano Rocca, Kumara Sastry, Stefania Solari -- Investigating Scaling of an Abstracted LCS Utilising Ternary and S-Expression Alphabets / Charalambos Ioannides, Will Browne -- Evolving Fuzzy Rules with UCS: Preliminary Results / Albert Orriols-Puig, Jorge Casillas, Ester Bernado-Mansilla -- Analysis of the System -- A Principled Foundation for LCS / Jan Drugowitsch, Alwyn M. Barry -- Revisiting UCS: Description, Fitness Sharing, and Comparison with XCS / Albert Orriols-Puig, Ester Bernado-Mansilla -- Mechanisms -- Analysis and Improvements of the Classifier Error Estimate in XCSF / Daniele Loiacono, Jan Drugowitsch, Alwyn Barry, Pier Luca Lanzi -- A Learning Classifier System with Mutual-Information-Based Fitness / Robert Elliott Smith, Max Kun Jiang -- On Lookahead and Latent Learning in Simple LCS / Larry Bull -- A Learning Classifier System Approach to Relational Reinforcement Learning / Drew Mellor -- Linkage Learning, Rule Representation, and the X-Ary Extended Compact Classifier System / Xavier Llora, Kumara Sastry, Claudio F. Lima, Fernando G. Lobo, David E. Goldberg -- New Directions -- Classifier Conditions Using Gene Expression Programming (Invited Paper) / Stewart W. Wilson -- Evolving Classifiers Ensembles with Heterogeneous Predictors / Pier Luca Lanzi, Daniele Loiacono, Matteo Zanini -- Substructural Surrogates for Learning Decomposable Classification Problems / Albert Orriols-Puig, Kumara Sastry, David E. Goldberg, Ester Bernado-Mansilla -- Empirical Evaluation of Ensemble Techniques for a Pittsburgh Learning Classifier System / Jaume Bacardit, Natalio Krasnogor -- Applications -- Technology Extraction of Expert Operator Skills from Process Time Series Data / Setsuya Kurahashi, Takao Terano -- Analysing Learning Classifier Systems in Reactive and Non-reactive Robotic Tasks / Renan C. Moioli, Patricia A. Vargas, Fernando J. Von Zuben -- Author Index. Publisher Marketing: 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."