Learning classifier systems

ABSTRACT

Broadly conceived as computational models of cognition and tools for modeling complex adaptive systems, later extended for use in adaptive robotics, and today also applied to effective classification and data-mining--what is a learning classifier system? How does it work? What's the theory behind its functioning? What are the most interesting research directions? What the applications? And what the relevant open issues? This introductory tutorial tries to answer these questions. It provides a gentle introduction to learning classifier systems, it overviews the theoretical understanding we have today, the current research directions, the most interesting applications, and the open issues.

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.0 GENERAL

General Terms:
Algorithms

Keywords:
genetics-based machine learning, machine learning, reinforcement learning, rule-based systems