A Decision-Theoretic Approach to Task Assistance for Persons with Dementia

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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