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Biomimetic Neural Learning for Intelligent Robots Intelligent Systems, Cognitive Robotics, and Neuroscience

   Author: creativelivenew1   |   06 February 2026   |   Comments icon: 0


Free Download Biomimetic Neural Learning for Intelligent Robots: Intelligent Systems, Cognitive Robotics, and Neuroscience by Stefan Wermter, Günther Palm, Mark Elshaw
English | PDF (True) | 2005 | 390 Pages | ISBN : 3540274405 | 8.2 MB
This book presents research performed as part of the EU project on biomimetic multimodal learning in a mirror neuron-based robot (MirrorBot) and contribu- tions presented at the International AI-Workshop on NeuroBotics. The over- all 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. This new type of robot is driven by recent new theories and experiments in neuroscience indicating that a biological and neuroscience-oriented approach could lead to new life-like robotic systems.


The book focuses on some of the research progress made in the MirrorBot project which uses concepts from mirror neurons as a basis for the integration of vision, language and action. In this book we show the development of new techniques using cell assemblies, associative neural networks, and Hebbian-type learning in order to associate vision, language and motor concepts. We have developed biomimetic multimodal learning and language instruction in a robot to investigate the task of searching for objects. As well as the research performed in this area for the MirrorBot project, the second part of this book incorporates significant contributions from other research in the field of biomimetic robotics. This second part of the book concentrates on the progress made in neuroscience inspired robotic learning approaches (in short: NeuroBotics).
We hope that this book stimulates and encourages new research in this in- teresting and dynamic area. We would like to thank all contributors to this book, all the researchers and administrative staff within the MirrorBot project, the reviewers of the chapters and all the participants at the AI-Workshop on NeuroBotics.
Finally, we would like to thank the EU for their support of the MirrorBot project, and Alfred Hofmann and his staff at Springer for their continuing sup- port.
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