2006-07-16Z2011-03-11T08:56:28Zhttp://cogprints.org/id/eprint/4961This item is in the repository with the URL: http://cogprints.org/id/eprint/49612006-07-16ZFrom motor babbling to hierarchical learning by imitation: a robot developmental pathwayHow does an individual use the knowledge
acquired through self exploration as a manipulable model through which to understand
others and benefit from their knowledge?
How can developmental and social learning be
combined for their mutual benefit? In this
paper we review a hierarchical architecture
(HAMMER) which allows a principled way
for combining knowledge through exploration
and knowledge from others, through the creation and use of multiple inverse and forward
models. We describe how Bayesian Belief Networks can be used to learn the association
between a robot’s motor commands and sensory consequences (forward models), and how
the inverse association can be used for imitation. Inverse models created through self
exploration, as well as those from observing
others can coexist and compete in a principled unified framework, that utilises the simulation theory of mind approach to mentally
rehearse and understand the actions of others.Yiannis DemirisAnthony Dearden