Advances in Computational Intelligence

1. Front Matter

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2. Lazy Meta-Learning: Creating Customized Model Ensembles on Demand

   • Piero P. Bonissone

   Pages 1-23

3. Multiagent Learning through Neuroevolution

   • Risto Miikkulainen, Eliana Feasley, Leif Johnson, Igor Karpov, Padmini Rajagopalan, Aditya Rawal et al.

   Pages 24-46

4. Reverse-Engineering the Human Auditory Pathway

   • Lloyd Watts

   Pages 47-59

5. Unpacking and Understanding Evolutionary Algorithms

   • Xin Yao

   Pages 60-76

6. Representation in Evolutionary Computation

   • Daniel Ashlock, Cameron McGuinness, Wendy Ashlock

   Pages 77-97

7. Quo Vadis, Evolutionary Computation?

   • Zbigniew Michalewicz

   Pages 98-121

8. Probabilistic Graphical Approaches for Learning, Modeling, and Sampling in Evolutionary Multi-objective Optimization

   • Vui Ann Shim, Kay Chen Tan

   Pages 122-144

9. The Quest for Transitivity, a Showcase of Fuzzy Relational Calculus

   • Bernard De Baets

   Pages 145-165

10. Cognition-Inspired Fuzzy Modelling

    • Maria Rifqi

    Pages 166-184

11. A Unified Fuzzy Model-Based Framework for Modeling and Control of Complex Systems: From Flying Vehicle Control to Brain-Machine Cooperative Control

    • Kazuo Tanaka

    Pages 185-208

12. Predictive Learning, Knowledge Discovery and Philosophy of Science

    • Vladimir Cherkassky

    Pages 209-233

13. Evolving Spiking Neural Networks and Neurogenetic Systems for Spatio- and Spectro-Temporal Data Modelling and Pattern Recognition

    • Nikola Kasabov

    Pages 234-260

14. Uncovering the Neural Code Using a Rat Model during a Learning Control Task

    • Chenhui Yang, Hongwei Mao, Yuan Yuan, Bing Cheng, Jennie Si

    Pages 261-279

15. Back Matter

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This state-of-the-art survey offers a renewed and refreshing focus on the progress in evolutionary computation, in neural networks, and in fuzzy systems. The book presents the expertise and experiences of leading researchers spanning a diverse spectrum of computational intelligence in these areas. The result is a balanced contribution to the research area of computational intelligence that should serve the community not only as a survey and a reference, but also as an inspiration for the future advancement of the state of the art of the field. The 13 selected chapters originate from lectures and presentations given at the IEEE World Congress on Computational Intelligence, WCCI 2012, held in Brisbane, Australia, in June 2012.

• attractive learning
• data mining
• evolutionary computation
• knowledge discovery
• neuroinformatics
• algorithm analysis and problem complexity

• Key Lab of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi’an, China

  Jing Liu

• Dipartimento di Elettronica e Informazione, Politecnico di Milano, Milano, Italy

  Cesare Alippi

• Université Pierre et Marie Curie - Paris 6, LIP6, Paris, France

  Bernadette Bouchon-Meunier

• Department of Electrical & Computer Engineering, Portland State University, Portland, USA

  Garrison W. Greenwood

• School of Engineering and Information Technology, University of New South Wales, Canberra, Australia

  Hussein A. Abbass

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