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Tuesday, May 5, 2020 | History

6 edition of Biomimetic Neural Learning for Intelligent Robots found in the catalog.

Biomimetic Neural Learning for Intelligent Robots

Intelligent Systems, Cognitive Robotics, and Neuroscience (Lecture Notes in Computer Science)

  • 131 Want to read
  • 24 Currently reading

Published by Springer .
Written in English

    Subjects:
  • Intelligence,
  • Neurosciences,
  • Programming - Systems Analysis & Design,
  • Congresses,
  • Computer Books: General,
  • Robots,
  • Computers,
  • Computers - General Information,
  • Neural networks (Computer science),
  • Machine learning,
  • Control systems,
  • Robotics,
  • Computers / Artificial Intelligence,
  • biomimetic robots,
  • cognitive development in robots,
  • cognitive robots,
  • imitation and neural networks,
  • learning for robots,
  • Artificial Intelligence - General,
  • General

  • Edition Notes

    ContributionsStefan Wermter (Editor), Günther Palm (Editor), Mark Elshaw (Editor)
    The Physical Object
    FormatPaperback
    Number of Pages383
    ID Numbers
    Open LibraryOL9055732M
    ISBN 103540274405
    ISBN 109783540274407

    Biomimetic robots differ from traditional robots in that they are agile, relatively cheap, and able to deal with real-world environments. The engineering of these robots requires a thorough understanding of the biological systems on which they are based, at both the biomechanical and physiological book provides an in-depth overview 4/5(1). Abstract 1 Introduction One learning approach that can make intelligent robots easy to use is imitation learning. Such learning allows the observer to gain skills by creating an abstract representation of the teacher's behaviour, and an understanding of the teacher's aims to produce the required solution.

    M. Elshaw obtained an MSc in Applied Artificial Intelligence from the University of Sunderland, UK in and MPhil using intelligent approaches to assess the performance of electronic odour sensing systems. Since , he has been a Research Assistant on the Emergent Neural Computational Architectures based on Neuroscience (EmerNet) and Biomimetic Multimodal Learning in a Mirror Cited by: Conference: Biomimetic Neural Learning for Intelligent Robots - Intelligent Systems, Cognitive Robotics, and Neuroscience John Christopher Murray Harry R. Erwin.

    Evolutionary, Neural, and Fuzzy Systems Biomimetic Neural Learning for Intelligent Robots: Intelligent Systems, Cognitive Robotics, and Neuroscience (Lecture Notes in Computer Science) Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms: Industrial Applications. Graphical Models: Principles and Techniques (Adaptive Computation and Machine Learning series) From Computer to Brain: Foundations of Computational Neuroscience Biomimetic Neural Learning for Intelligent Robots: Intelligent Systems, Cognitive Robotics, and Neuroscience (Lecture Notes in.


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Biomimetic Neural Learning for Intelligent Robots: Intelligent Systems, Cognitive Robotics, and Neuroscience (Lecture Notes in Computer Science ()): Medicine & Health Science Books @ Biomimetic Neural Learning for Intelligent Robots Intelligent Systems, Cognitive Robotics, and Neuroscience.

Editors: Wermter, Stefan, Palm, Günther, Elshaw, Mark. This state-of-the-art survey contains selected papers contributed by researchers in intelligent systems, cognitive robotics, and neuroscience including contributions from the MirrorBot project and from the NeuroBotics Workshop The research work presented demonstrates significant novel Price: $ behavior biomimetic robots cognitive robots imitation and neural net intelligent systems learning learning for robots learning self localization and mapping neural networks for robots neural vision robot robotics speech interfaces and neural networks spiking neural networks in robots talking robots.

The overall aim of the book is to present a broad spectrum of current research into biomimetic neural learning for intelligent autonomous robots. There is a need for a new type of robot which is inspired by nature and so performs in a more flexible learned manner than current robots.

The overall aim of the book is to present a broad spectrum of current research into biomimetic neural learning for intelligent autonomous robots. There is a need for a new type of robots which is inspired by nature and so performs in a more flexible learned manner than current robots.

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 by: 4.

(PDF) Towards Biomimetic Neural Learning for Intelligent Robots | Stefan Wermter - 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. This chapter explores modular learning in artificial neural networks for intelligent robotics.

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Biomimetic Neural Learning for Intelligent Robots: Intelligent Systems, Cognitive Robotics, and Neuroscience (Lecture Notes in Computer Science / Lecture Notes in Artificial Intelligence) (1st Edition) by Stefan Wermter (Editor), Mark Elshaw (Editor), Günther Palm (Editor), Gunther (Editor) Palm, G&Radic Palm Paperback, Pages, Published ISBN / ISBN Book Edition: 1st Edition.

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The research work presented demonstrates significant novel developments in biologically inspired neural models for use in intelligent robot environments and biomimetic cognitive behavior.". Home Browse by Title Books Biomimetic Neural Learning for Intelligent Robots: intelligent systems, cognitive robotics, and neuroscience Combining visual attention, object recognition and associative information processing in a neurobotic system.

BibTeX @ARTICLE{Wermter05groundingneural, author = {Stefan Wermter and Cornelius Weber and Mark Elshaw and Vittorio Gallese and Friedemann Pulvermüller}, title = {Grounding neural robot language in action. Biomimetic Neural Learning for Intelligent Robots}, journal = {Intelligent Systems, Cognitive Robotics, and Neuroscience}, year = {}, pages = {}}.

Artificial Intelligence and Robotics // InArtificial Intelligence (AI) celebrated its 60th anniversary of the Dartmouth Workshop, which marked the beginning of AI being recognised as an academic discipline.

One year on, the pace of AI has captured the wildest imagination of both the scientific community and the general by: 1. Biomimetic Neural Learning for Intelligent Robots: intelligent systems, cognitive robotics, and neuroscience A spiking neural network model of multi-modal language processing of robot .Intelligent Investor, Stock Market, Financial Freedom, Stock Valuation, Wealth Creation Book 1) Biomimetic Neural Learning for Intelligent Robots: Intelligent Systems, Cognitive Robotics, and Neuroscience (Lecture Notes in Computer Science) The Not-So-Intelligent Designer: Why EvolutionFile Size: KB.Book Chapter A.

Vardy and F. Oppacher. A scale invariant local image descriptor for visual homing. In G. Palm and S. Wermter, editors, Biomimetic neural learning for intelligent robots.

Springer, [PDF Document] Refereed Proceedings A. Vardy. Using Feature Scale Change for Robot Localization along a .