From exploration to imitation: using learnt internal models to imitate others

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Title: From exploration to imitation: using learnt internal models to imitate others
Authors: Dearden, A
Demiris, Y
Item Type: Conference Paper
Abstract: We present an architecture that enables asocial and social learning mechanisms to be combined in a unified framework on a robot. The robot learns two kinds of internal models by interacting with the environment with no a priori knowledge of its own motor system: internal object models are learnt about how its motor system and other objects appear in its sensor data; internal control models are learnt by babbling and represent how the robot controls objects. These asocially-learnt models of the robot’s motor system are used to understand the actions of a human demonstrator on objects that they can both interact with. Knowledge acquired through self-exploration is therefore used as a bootstrapping mechanism to understand others and benefit from their knowledge.
Issue Date: 30-Apr-2007
Publisher: AISB
Start Page: 218
End Page: 226
Copyright Statement: © 2007 AISB
Conference Name: AISB'07: Artificial and Ambient Intelligence
Conference Location: Newcastle, UK
Publication Status: Published
Publisher URL:
Start Date: 2007-04-02
Finish Date: 2007-04-04
Conference Place: Newcastle, UK
Appears in Collections:Electrical and Electronic Engineering

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