Abstract:* To build an autonomous cognitive agent is a very challenging
goal. Crucial to the ultimate attainment of this aim is an ability to
perceive, understand, formulate hypotheses and act based on the agent's
perceptions. I will discuss work undertaken at Leeds in pursuit of this
goal. A key focus of our work is to integrate quantitative and qualitative
modes of representation and to learn as much as possible of any domain
specific models required to understand and operate in a specific situation.
As one example of our approach, I will show how functional object categories
can be learned by mining qualitative spatio-temporal models of behaviour.

*Biography:* Tony Cohn holds a Personal Chair at the University of Leeds,
where he is Professor of Automated Reasoning and served a term as Head of
the School of Computing August 1999 -- July 2004. He holds BSc and PhD
degrees from the University of Essex where he studied under Pat Hayes. He
spent 10 years at the University of Warwick before moving to Leeds in 1990.
He now leads a research group working on Knowledge Representation and
Reasoning with a particular focus on qualitative spatial/spatio-temporal
reasoning. His current research interests range from theoretical work on
spatial calculi and spatial ontologies, to cognitive vision, modelling
spatial information in the hippocampus, and integrating utility data
recording the location of underground assets. He has been Chairman/President
of the UK AI Society SSAISB, the European Coordinating Committee on AI
(ECCAI), KR inc, the IJCAI Board of Trustees and is currently
Editor-in-Chief of the AAAI Press, and of the journals Spatial Cognition and
Computation, and Artificial Intelligence.