1. Learning Classifier Systems

   • Larry Bull
   • Pler Luca Lanzi
   • Wolfgang Stolzmann

   Editorial Pages: 143 - 143

2. An algorithmic description of XCS

   • M. V. Butz
   • S. W. Wilson

   Focus Pages: 144 - 153

3. On accuracy-based fitness

   • L. Bull

   Focus Pages: 154 - 161

4. Learning classifier systems from a reinforcement learning perspective

   • P. L. Lanzi

   Focus Pages: 162 - 170

5. What should a classifier system learn and how should we measure it?

   • T. Kovacs

   Focus Pages: 171 - 182

6. The stability of long action chains in XCS

   • A. M. Barry

   Focus Pages: 183 - 199

7. An accuracy based corporate classifier system

   • A. Tomlinson
   • L. Bull

   Focus Pages: 200 - 215

8. YACS: a new learning classifier system using anticipation

   • P. Gérard
   • W. Stolzmann
   • O. Sigaud

   Focus Pages: 216 - 228

9. Robustness in organizational-learning oriented classifier system

   • K. Takadama
   • S. Nakasuka
   • K. Shimohara

   Focus Pages: 229 - 239

10. Learning classifier systems resources

    • T. Kovacs

    Focus Pages: 240 - 243

11. A dynamically-constructed fuzzy neural controller for direct model reference adaptive control of multi-input-multi-output nonlinear processes

    • Y. Frayman
    • L. Wang

    Original paper Pages: 244 - 253

12. Some convergence results in Dempster–Shafer theory

    • C. Roesmer

    Original paper Pages: 254 - 257

13. Interpolation and extrapolation of fuzzy quantities – the multiple-dimensional case

    • S. Jenei
    • E. P. Klement
    • R. Konzel

    Original paper Pages: 258 - 270

14. An fMUX architecture: data modularization and mixed-mode system modeling

    • W. Pedrycz
    • G. Vukovich

    Original paper Pages: 271 - 276

15. Applying genetic algorithms to game search trees

    • T.-P. Hong
    • K.-Y. Huang
    • W.-Y. Lin

    Original paper Pages: 277 - 283