Associative Neural Models for Biomimetic Multi-modal Learning in a Mirror Neuron-based Robot
Modeling Language, Cognition and Action. Proceedings of the Ninth Neural Computation and Psychology Workshop University of Plymouth, UK, 8 – 10 September 2004,
Editors: Cangelosi, Angelo; Bugmann, Guido; Borisyuk, Roman,
Volume 16,
pages 31--46,
doi: 10.1142/9789812701886_0003
- May 2005
By using neurocognitive evidence on mirror neuron system concepts the MirrorBot
project has developed neural models for intelligent robot behaviour. These models
employ diverse learning approaches such as reinforcement learning, self-organisation and
associative learning to perform cognitive robotic operations such as language grounding
in actions, object recognition, localisation and docking. In this paper we describe
architectures based on an associative self-organising framework which were designed to
combine multimodal inputs of language, vision and motor programs to produce complex
robot behaviours.
@InProceedings{WWE05, author = {Wermter, Stefan and Weber, Cornelius and Elshaw, Mark I.}, title = {Associative Neural Models for Biomimetic Multi-modal Learning in a Mirror Neuron-based Robot}, booktitle = {Modeling Language, Cognition and Action. Proceedings of the Ninth Neural Computation and Psychology Workshop University of Plymouth, UK, 8 – 10 September 2004}, editors = {Cangelosi, Angelo; Bugmann, Guido; Borisyuk, Roman}, number = {}, volume = {16}, pages = {31--46}, year = {2005}, month = {May}, publisher = {World Scienific}, doi = {10.1142/9789812701886_0003}, }