Now showing items 1-3 of 3

  • Artificial biochemical networks: a different connectionist paradigm. 

    Macleod, Christopher; Capanni, Niccolo Francesco (Springer. The original publication is available at www.springerlink.com http://dx.doi.org/10.1007/s10462-009-9149-y, 2010-02)
    MACLEOD, C. and CAPANNI, N. F., 2010. Artificial biochemical networks: a different connectionist paradigm. Artificial Intelligence Review , 33 (1/2), pp. 123-134.
    Connectionist models are usually based on Artificial Neural Networks. However, there is another route towards Parallel Distributed Processing. This is by considering the origins of the intelligence displayed by the single ...
  • Incremental growth in modular neural networks. 

    Macleod, Christopher; Maxwell, Grant M.; Muthuraman, Sethuraman (Elsevier http://dx.doi.org/10.1016/j.engappai.2008.11.002, 2009-06)
    MACLEOD, C., MAXWELL, G. M., and MUTHURAMAN, S., 2009. Incremental growth in modular neural networks. Engineering Applications of Artificial Intelligence, 22 (4/5), pp. 660-666.
    This paper outlines an algorithm for incrementally growing Artificial Neural Networks. The algorithm allows the network to expand by adding new sub-networks or modules to an existing structure; the modules are trained using ...
  • Multivariate Markov networks for fitness modelling in an estimation of distribution algorithm. 

    Brownlee, Alexander Edward Ian (The Robert Gordon University School of Computing, 2009-05)
    A well-known paradigm for optimisation is the evolutionary algorithm (EA). An EA maintains a population of possible solutions to a problem which converges on a global optimum using biologically-inspired selection and ...