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.
|Publication status||Published - 2005|
|Event||International Joint Conference on Artificial Intelligence - Edinburgh, United Kingdom|
Duration: 30 Jul 2005 → 5 Aug 2005
|Conference||International Joint Conference on Artificial Intelligence|
|Period||30/07/05 → 5/08/05|