Jennifer Boger
IBBME
University of Toronto
email: jen.boger@utoronto.ca
Pascal Poupart
Department of Computer Science
University of Waterloo
email: ppoupart@cs.uwaterloo.ca
Jesse Hoey
Department of Computer Science
University of Toronto
Toronto, ON M5S 3H5
email: jhoey@cs.toronto.edu
Craig Boutilier
Department of Computer Science
University of Toronto
Toronto, ON M5S 3H5
email: cebly@cs.toronto.edu
Geoff Fernie
Toronto Rehabilitation Institute
email: Fernie.Geoff@torontorehab.on.ca
Alex Mihailidis
Department of Occupational Therapy
University of Toronto
Toronto, ON
email: alex.mihailidis@utoronto.ca
Abstract
Cognitive assistive technologies that aid people
with dementia (such as Alzheimer’s disease) hold
the promise to provide such people with an increased
level of independence. However, to realize
this promise, such systems must account for
the specific needs and preferences of individuals.
We argue that this form of customization requires
a sequential, decision-theoretic model of interaction.
We describe both fully and partially observable
Markov decision process (POMDP) models of
a handwashing task, and show that, despite the potential
computational complexity, these can be effectively
solved and produce policies that are evaluated
as useful by professional caregivers.
To appear, IJCAI-05
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