CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
L0—the first five years of an automated language acquisition project
Artificial Intelligence Review - Special issue: grounding representations
Self-organizing maps
The origins of syntax in visually grounded robotic agents
Artificial Intelligence - Special issue: artificial intelligence 40 years later
Experiences with an interactive museum tour-guide robot
Artificial Intelligence - Special issue on applications of artificial intelligence
Towards the networks of the brain: from brain imaging to consciousness
Neural Networks - Special issue on organisation of computation in brain-like systems
A Context-Dependent Attention System for a Social Robot
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Socially embedded learning of the office-conversant mobile robot Jijo-2
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Grounding neural robot language in action
Biomimetic Neural Learning for Intelligent Robots
Simulating meaning negotiation using observational language games
EELC'06 Proceedings of the Third international conference on Emergence and Evolution of Linguistic Communication: symbol Grounding and Beyond
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In the MirrorBot project we examine perceptual processes using models of cortical assemblies and mirror neurons to explore the emergence of semantic representations of actions, percepts and concepts in a neural robot. The hypothesis under investigation is whether a neural model will produce a life-like perception system for actions. In this context we focus in this paper on how instructions for actions can be modeled in a self-organising memory. Current approaches for robot control often do not use language and ignore neural learning. However, our approach uses language instruction and draws from the concepts of regional distributed modularity, self-organisation and neural assemblies. We describe a self-organising model that clusters actions into different locations depending on the body part they are associated with. In particular, we use actual sensor readings from the MIRA robot to represent semantic features of the action verbs. Furthermore, we outline a hierarchical computational model for a self-organising robot action control system using language for instruction.