Abstract :
Theoretical models have purposes like providing quantitative descriptions, aiding the critical analysis of hypotheses and the understanding of biological mechanisms, and assisting in the prediction of behaviours and design of experiments. By contrast, AIS are more concerned with efficient problem-solving. This conceptual paper demonstrates that even these more abstract and simplified "models" of natural systems may present some patterns of behaviour that are similar to those observed in experimental and theoretical models. To do so, a dynamical analysis of a particular artificial immune network, aiNet, will be performed and discussed. Although very simplistic, this model will be demonstrated to present primary, secondary, and cross-reactive immune responses. A discussion about the role of network metadynamics is also provided.
Keywords :
artificial intelligence; biocybernetics; artificial immune network; behaviour prediction; biological mechanisms; design of experiment; dynamical analysis; efficient problem-solving; immune response; natural systems; network metadynamics; Ant colony optimization; Biological neural networks; Biological system modeling; Biology computing; Computational intelligence; Humans; Immune system; Performance analysis; Predictive models; Problem-solving;