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Tutorials: Nov 13, 2011, Shanghai, China
Main Conference: Nov 14-17, 2011, Shanghai, China
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Special Session on Integrating Multiple Nature-inspired Approaches

Organizers:

Shan He
Cercia, School of Computer Science, University of Birmingham, UK.
E-mail: s.he@cs.bham.ac.uk


Xin Yao
Cercia, School of Computer Science, University of Birmingham, UK.
E-mail: x.yao@cs.bham.ac.uk


Description:

Nature inspired computation is a fast growing research paradigm, which draws inspirations from nature to design efficient computational techniques. In the past few decades, this research field has seen many breakthroughs in theoretical studies and many successful applications to complex real-world problems. However, most research so far has focused on individual paradigms, e.g., neural computation, evolutionary computation, etc. Few studies are on how to integrate different techniques together, what roles each technique plays in an integrate system and why an integrate system works (or fails). The ICONIP2011 special session on “Integrating Multiple Nature-inspired Approaches�aims to bring together researchers to report their original and unpublished work on theories, experiments, and applications of integrating multiple nature inspired computational approaches.

Topics of interest include but not limited to:

We invite paper submissions on any aspect of integrating multiple nature inspired computational approaches, including neural networks, evolutionary algorithms, swarm intelligence, self-organised and fully-decentralised systems, artificial organisms, co-evolution, etc. Topics of interest include, but are not limited to:

  1. When can an integrated system consisting of multiple nature inspired computational approaches perform well, and why?
  2. What are relationships between swarm intelligence and ensembles of learning machines? What are the similarities and differences?
  3. What are the fundamental differences among different nature inspired computational approaches? What roles do they play in an integrated system?
  4. What inspirations can we draw from natural systems (biological, ecological, social, physical, chemical, etc.) in integrating different computational approaches?
  5. What are the relationships between nature inspired optimisation and nature inspired learning? How does such relationship influence the potential integration of different nature inspired computational approaches?
  6. What are the most appropriate applications of integrated nature inspired computational approaches?
Biographies:

        Shan He

        Cercia, School of Computer Science, University of Birmingham, UK.

        Email: s.he@cs.bham.ac.uk


        Xin Yao

        Cercia, School of Computer Science, University of Birmingham, UK.

        Email: x.yao@cs.bham.ac.uk



 
         
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