IFIP TC12 - Artificial Intelligence - IFIP TC12 - Artificial Intelligence

  • WG 12.9 – Computational Intelligence

    Officers

    Chair

    Prof. Tharam Dillon, La Trobe University, Melbourne, Australia e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

    Vice-Chairs

    Prof. Elizabeth Chang, Curtin University, Perth, Australia e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
    Dr. Vasile Palade, Dept. of Computer Science, University of Oxford, Oxford, United Kingdom, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
    Dr. Masoud Nikravesh, University of California Berkeley, CA, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.  

    Secretary

    Dr. Kit Yan Chan, Curtin University, Perth, Australia e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

    Aim

    To obtain a deeper understanding of Computational Intelligence and its Applications and help in the development of its theoretical foundations and technological underpinnings.

    Scope

    The scope of the Working Group’s activities includes (but is not restricted to) the following:

    1. Novel concepts of computational Intelligence approaches and their adaptation for handling real world applications.
    2. Investigation of techniques of modification of computational Intelligence approaches so as to produce more effective computational Intelligence approaches.
    3. Enhancement of the computational Intelligence approaches by co-operating with classical or statistical methods.
    4. Using computational Intelligence approaches for handling constrained, multi-objective and large scale optimization problems for real world applications.
    5. Application of computational Intelligence approaches in real industrial applications
    6. Parallel computational Intelligence approaches for practical applications in real world.
    7. Using computational Intelligence approaches for solving dynamic optimization or time-varying problems in real world.
    8. The following computational intelligence approaches include, but are not limited to:
      • Neural Networks
      • Fuzzy Systems
      • Evolutionary Computation
      • Particle swarm optimization
      • Multi-agent systems
      • Intelligent control systems
      • Support vector machine
      • Bayesian networks
      • Global and constrained optimization