On the Emergence of Novel Behaviours From Complex Non Linear Systems

Lorenzo Riano, TM McGinnity

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    Emergent behaviours are believed to be a property of complex cognitive architectures. However it is difficult to observe them in carefully engineered systems. We believe that, in order to obtain interesting and surprising behaviours, the designer has to remove some predictability requirements. To explore this we studied how the complexity, defined according to the Kolmogorov theory, is linked to truly emergent behaviours. This study has been conducted on a real robot driven by the non-linear dynamics of a recurrent neural network created using evolutionary approaches. In several experiments we found that, while a simple network is equivalent to a deterministic automata, networks of increasing complexity exhibit novel behaviours. This is due to a spontaneous background activity of the neurons which can be sustained only by a complex network. These results support the idea that in a non predictable architecture novel and surprising cognitive capabilities emerge in a natural way.
    Original languageEnglish
    Title of host publicationUnknown Host Publication
    PublisherIOS Press
    Number of pages10
    Publication statusPublished (in print/issue) - 2010
    EventProceeding of BICA 2010, International Conference on Biological Inspired Cognitive Architectures -
    Duration: 1 Jan 2010 → …

    Conference

    ConferenceProceeding of BICA 2010, International Conference on Biological Inspired Cognitive Architectures
    Period1/01/10 → …

    Keywords

    • cognitive robotics
    • genetic algorithms
    • neural networks
    • non linear

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