V. Tikhanoff
2011
Autonomous Mental Development, IEEE Transactions on 3(1):17--29, 2011
Abstract Building intelligent systems with human level competence is the ultimate grand challenge for science and technology in general, and especially for cognitive developmental robotics. This paper proposes a new approach to the design of cognitive skills in a robot ...
2009
Neural Networks 22(5):579--585, 2009
The issue of how children learn the meaning of words is fundamental to developmental psychology. The recent attempts to develop or evolve efficient communication protocols among interacting robots or virtual agents have brought that issue to a central place in ...
2007
Integrating language and cognition: A cognitive robotics approach
Computational Intelligence Magazine, IEEE 2(3):65--70, 2007
Abstract In this paper, we present some recent cognitive robotics studies on language and cognition integration to demonstrate how the language acquired by robotic agents can be directly grounded in action representations. These studies are characterized by the ...
2006
IJCNN 2006, pages 1576-1582, 2006
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 ...MORE ⇓
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.