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1
Assisted Cognition
Henry Kautz, Oren Etzioni, & Dieter FoxUniversity of Washington
Department of Computer Science & Engineering
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An Epidemic of Alzheimer’s
4.6 million people in the US with Alzheimer’s16 million people by 2050Today costs $100 billion @ year for care
Additional $61 billion in lost productivity from family members
$ ½ Trillion total cost by 2050!Projections even worse for Japan and Europe
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Cognition in ContextCan often compensate for physical disabilities by change in environment
WheelchairsRedesigned appliances
Cognitive competence also depends on environment
Can you cook dinner, given a dead animal, a stone knife, and set of flints?
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ProblemCaregiver burnout
½ of all family caregivers suffer depression“The 36 Hour Day”
Far too few professional caregivers to provide constant 1-on-1 help in institutional settings
Already a nationwide shortage of good staff
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Vision
Understanding human behavior from low-level sensory data
Using commonsense knowledgeLearning individual user models
Actively offering prompts and other forms of help as neededAlerting human caregivers when necessary
Computer systems that improve the independence and safety of people suffering from cognitive limitations by…
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Model-Based Interpretation
General approach: build a probabilistic model of– Common user goals– Plans (complex behaviors) that achieve those goals
• Feasibility constraints • Temporal constraints• Failure (abnormality) modes
– How simple behaviors are sensed
Run model “backwards” to interpret sensed data
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Activity Compass Zero-configuration personal
guidance system Learns model of user’s
travel on foot, by public transit, by bike, by car
Predicts user’s next destination, offers proactive help if lost or late
Integrates user data with external constraints Maps, bus schedules,
calendars, … EM approach to clustering
& segmenting data
The Activity Compass Don Patterson, Oren Etzioni, and Henry Kautz (2003)
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Scenario IJoe gets off the bus on the way to the community center.He can’t remember which way to walk.He consults his Activity Compass. It has predicted his destination based on past behavior, and guides him to the community center.
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Scenario IIJoe has a regular physical therapist’s appointment at 2 pm.Compass alerts Joe that he will need to leave home in 10 minutes to catch the usual bus there.Joe fails to leave in time. Compass asks whether goal of going to physical therapist is valid.If answer is affirmative, Compass creates alternative plan to get Joe there as soon as possible.
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Data Source: Elite Care Residences
Elite Care is the realization of our dream to provide a fundamentally different approach to assisted living. Extended Family Residences promote a family lifestyle of close staff-resident relationships, meaningful community-building activities, and physical and mental achievement while providing assistance when needed… Technology helps us maintain our family environment by allowing us to the focus on residents…
- Lydia Lundberg & Bill Reed
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Activity of daily living monitor & prompter
Foundations of Assisted Cognition Systems. Kautz, Etzioni, Fox, Weld, and Shastri, 2003
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Recognizing unexpected events using online model selection
User errors, abnormal behavior
Select model that maximizes likelihood of data: Generic model User-specific model Corrupt (impaired) user
model Neurologically-plausible
corruptions Repetition Substitution Stalling
Fox, Kautz, & Shastri (forthcoming)
fill kettleput kettleon stove
fill kettleput kettleon stove
put kettlein closet
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Technical Foundations
Hidden Markov models– Mathematical framework for describing processes
with hidden state that must be inferred from observations
Hierarchical plan networks– Represents how a task can be broken down into
subtasksHierarchical hidden Markov models*– Key to climbing food-chain!
* Precisely speaking: factorial hierarchical hidden semi-Markov models