Show Reference: "Towards Biomimetic Neural Learning for Intelligent Robots"

Towards Biomimetic Neural Learning for Intelligent Robots In Biomimetic Neural Learning for Intelligent Robots, Vol. 3575 (2005), pp. 1-18, doi:10.1007/11521082_1 by Stefan Wermter, Günther Palm, Cornelius Weber, Mark Elshaw edited by Stefan Wermter, Günther Palm, Mark Elshaw
@incollection{wermter-et-al-2005,
    abstract = {We present a brief overview of the chapters in this book that relate to the development of intelligent robotic systems that are inspired by neuroscience concepts. Firstly, we concentrate on the research of the {MirrorBot} project which focuses on biomimetic multimodal learning in a mirror neuron-based robot. This project has made significant developments in biologically inspired neural models using inspiration from the mirror neuron system and modular cerebral cortex organisation of actions for use in an intelligent robot within an extended 'pick and place' type scenario. The hypothesis under investigation in the {MirrorBot} project is whether a mirror neuron-based cell assembly model can produce a life-like perception system for actions. Various models were developed based on principles such as cell assemblies, associative neural networks, and Hebbian-type learning in order to associate vision, language and motor concepts. Furthermore, we introduce the chapters of this book from other researchers who attended our {AI}-workshop on {NeuroBotics}.},
    author = {Wermter, Stefan and Palm, G\"{u}nther and Weber, Cornelius and Elshaw, Mark},
    booktitle = {Biomimetic Neural Learning for Intelligent Robots},
    doi = {10.1007/11521082\_1},
    editor = {Wermter, Stefan and Palm, G\"{u}nther and Elshaw, Mark},
    keywords = {biomimetic, neurorobotics, philosophical, research, robotics},
    pages = {1--18},
    posted-at = {2013-06-27 11:44:05},
    priority = {2},
    publisher = {Springer Berlin Heidelberg},
    series = {Lecture Notes in Computer Science},
    title = {Towards Biomimetic Neural Learning for Intelligent Robots},
    url = {http://dx.doi.org/10.1007/11521082\_1},
    volume = {3575},
    year = {2005}
}

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Taking inspiration for technical solutions from nature promises greater robustness.

Biomimetic (neural) robotics can provide feedback to neuroscience.