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Evolutionary Rule-based Machine Learning

Nineteenth International Workshop on Learning Classifier Systems

 

Call for Papers

International Workshop on Evolutionary Rule-based Machine Learning (former Nineteenth International Workshop on Learning Classifier Systems) will be held in Denver, USA during the Genetic and Evolutionary Computation Conference (GECCO-2016), July 20-24, 2016.

Originally, Learning Classifier Systems (LCSs) were introduced by John H. Holland as a way of applying evolutionary computation to machine learning and adaptive behavior problems. Since then, the LCS paradigm has broadened greatly into a framework that encompasses many representations, rule discovery mechanisms, and credit assignment schemes.

Current LCS applications range from data mining, to automated innovation and the on-line control of cognitive systems. LCS research includes various actual system approaches: While Wilson’s accuracy-based XCS system (1995) has received the highest attention and gained the highest reputation, studies and developments of other LCSs are usually discussed and contrasted. Advances in machine learning, and reinforcement learning in particular, as well as in evolutionary computation have brought LCS systems the necessary competence and guaranteed learning properties. Novel insights in machine learning and evolutionary computation are being integrated into the LCS framework.

Thus, we invite submissions that discuss recent developments in all areas of research on, and applications of, Learning Classifier Systems. IWLCS is the event that brings together most of the core researchers in classifier systems. The workshop also provides an opportunity for researchers interested in LCSs to get an impression of the current research directions in the field as well as a guideline for the application of LCSs to their problem domain.

This year the workshop is presented under the title of Evolutionary Rule-based Machine Learning to broaden the scope and encourage wider participation.

Topics of interests include but are not limited to:

  • Paradigms of LCS (Michigan, Pittsburgh, …)
  • Theoretical developments (behavior, scalability and learning bounds, …)
  • Representations (binary, real-valued, oblique, non-linear, fuzzy, …)
  • Types of target problems (single-step, multiple-step, regression/function approximation,…)
  • System enhancements (competent operators, problem structure identification and linkage learning, …)
  • LCS for Cognitive Control (architectures, emergent behaviours, …)
  • Applications (data mining, medical domains, bioinformatics, …)
  • Optimizations and parallel implementations (GPU, matching algorithms, …)

Submission and Publication

Submissions will be short-papers up to 8 pages in ACM format. Please see the GECCO 2015 information for authors for further details. However, unlike GECCO, papers do not have to be submitted in anonymous format.

All accepted papers will be presented at IWLCS 2015 and will appear in the GECCO workshop volume, which will be published by ACM (Association for Computing Machinery). Authors will be invited after the workshop to submit revised (full) papers that, after a thorough review process, are to be published in a special issue of the Evolutionary Intelligence journal.

All papers should be submitted in PDF format and e-mailed to: iwlcssubmissions@gmail.com

Important dates

  • April, 03, 2016 – Paper submission deadline
  • April, 20, 2016 – Notification to authors
  • May,  04, 2016 – Camera-ready Submission
  • July 20-24, 2016 – GECCO 2016 Conference

Organizing Committee

  • Karthik Kuber, Microsoft, US.
    (karthik.kuber@microsoft.com)
  • Masaya Nakata, The University of Electro-Communications, Japan.
    (k.shafi@adfa.edu.au)
  • Kamran Shafi, University of New South Wales, Australia.
    (k.shafi@adfa.edu.au)

Advisory Committee

  • Jaume Bacardit, University of Nottingham (UK)
  • Ester Bernadó-Mansilla, Universitat Ramon Llull (Spain)
  • Will Browne, Victoria University of Wellington (NZ)
  • Martin V. Butz, Universitat Wurzburg (Germany)
  • Muhammad Iqbal, Victoria University of Wellington
  • Jan Drugowitsch, University of Rochester (USA)
  • Tim Kovacs, University of Bristol (UK)
  • Pier Luca Lanzi, Politecnico di Milano (Italy)
  • Xavier Llorà, University of Illinois at Urbana-Champaign (USA)
  • Wolfgang Stolzmann, Daimler Chrysler AG (Germany)
  • Ryan J. Urbanowicz, Dartmouth College
  • Kamran Shafi, University of New South Wales
  • Keiki Takadama, Tokyo Institute of Technology (Japan)
  • Stewart Wilson, Prediction Dynamics (USA)