dealing with uncertainty the need to deal with uncertainty arose in “expert systems” code...
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Dealing with Uncertainty The need to deal with uncertainty arose in “expert systems”
Code expertise into a computer systemExample: Medical diagnosis: MYCIN Equipment failure diagnosis in a factory
Sample from MYCIN: IF
The infection is primary-bacteremia AND The site of the culture is one of the sterile sites AND The suspected portal of entry is the gastrointestinal tract
THEN There is suggestive evidence (70%) that the infection is bacteroid
Expert systems often have long chains IF X THEN Y … IF Y THEN Z … IF Z THEN W … If uncertainty is not handled correctly, errors build up, wrong diagnosis Also, there may be dependencies, e.g. X and Y depend on each other Leads to more errors…
Need a proper way to deal with uncertainty
How do Humans Deal with Uncertainty? Not very well…
Consider a form of cancer which afflicts 0.8% of people (rare) A lab has a test to detect the cancer The test has a 98% chance to give an accurate result Mr. Bloggs goes for the test
The result comes back positive i.e. the test says he has cancer
What is the chance that he has the cancer? 28%
Afflicts experts too Studies have shown: human experts thinking of likelihoods do not reason
like mathematical probability
A
B C
D E
Increased total serum count
Metastatic cancer
Brain Tumour
Severe headachesComa
No Link
A
B C
D E
Increased total serum count
Metastatic cancer
Brain Tumour
Severe headachesComa
Serum count
Brain tumour
Coma
Yes Yes 95%
Yes No 94%
No Yes 29%
No No 0.1%
Brain tumour
headache
Yes 70%
No 1%
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Inference in Belief Networks Questions for a belief network:
Diagnosis Work backwards from some evidence to a hypothesis
Causality Work forwards from some hypothesis to likely evidence Test a hypothesis, find likely symptoms
In general – mixed mode Give values for some evidence variables Ask about values of others
No other approach handles all these modes
Reasoning can take some time Need to be careful to design network Local structure: few connections
How Good are Belief Networks? Relieves you from coding all possible dependencies
How many possibilities if full network?
Tools are available Build network graphically System handles mathematical probabilities
Case study: Pathfinder a medical expert system
Assists pathologists with diagnosis of lymph-node diseases Pathfinder is a pun
User enters initial findings Pathfinder lists possible diseases User can
Enter more findings Ask pathfinder which findings would narrow possibilities
Pathfinder refines the diagnosis Pathfinder version based on Belief Networks performs significantly better
than human pathologists