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IJCNN
2006
IEEE

Language Acquisition and Symbol Grounding Transfer with Neural Networks and Cognitive Robots

10 years 8 months ago
Language Acquisition and Symbol Grounding Transfer with Neural Networks and Cognitive Robots
— Neural networks have been proposed as an ideal cognitive modeling methodology to deal with the symbol grounding problem. More recently, such neural network approaches have been incorporated in studies based on cognitive agents and robots. In this paper we present a new model of symbol grounding transfer in cognitive robots. Language learning simulations demonstrate that robots are able to acquire new action concepts via linguistic instructions. This is achieved by autonomously transferring the grounding from directly grounded action names to new higher-order composite actions. The robot’s neural network controller permits such a grounding transfer. The implications for such a modeling approach in cognitive science and autonomous robotics are discussed.
Angelo Cangelosi, Emmanouil Hourdakis, Vadim Tikha
Added 11 Jun 2010
Updated 11 Jun 2010
Type Conference
Year 2006
Where IJCNN
Authors Angelo Cangelosi, Emmanouil Hourdakis, Vadim Tikhanoff
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