RE: Model and sources of uncertainty

> Dissonance happens when you have distinct pieces of evidence
> supporting contradictory or conflicting views.
> If a given piece of evidence supports hypothesis H and another
> supports hypothesis notH, then we have contradiction, since H and
> notH are mutually exclusive. A Knowledge Base that has two axioms
> supporting contradictory hypothesis is inconsistent.
> Conflicting evidence is another form of dissonance, this time
> supporting hypothesis that are not mutually exclusive. Therefore, a
> Knowledge Base that has two pieces of evidence supporting conflicting
> hypothesis is not necessarily inconsistent.
> Ambiguity happens when you have one or more pieces of evidence that
> are subject to different interpretations, which can lead to distinct,
> sometimes incompatible conclusions.

[VK] I guess, we need to model "evidence" and "interpretation" as well in our
ontology in addition to agent, statement, belief and uncertainty

It's interesting how different notions of uncertainty presented above depend on
the notion of "evidence" and "interpretation". BTW, at this time my position on
these definitions is "uncertain", but I do find them clarifying and interesting.

> In other words, dissonance (either contradiction of conflict) refers
> to the relationship between distinct pieces of evidence, whereas
> ambiguity is more related to how a given piece of evidence is
> interpreted. To explore this idea further, two pieces of evidence may
> not be ambiguous (each one is clearly supporting a specific
> hypothesis), but they might be dissonant when analyzed together.

[VK] So looks like you are identifying the underlying causes of uncertainty
rather than the various types of uncertainty themselves?

> In short, if we see uncertainty as the inability to predict the
> outcome of an event, then such inability can be caused either by our
> imperfect knowledge on the event or by the nature of the event
> itself. 

[VK] What about the case where imperfect knowledge about an event can lead to
the prediction of a certain event?

For e.g., If the patient's blood pressure is between X and Y then the doctor
will prescribe ACE Inhibitors.

So the event(or knowledge thereof) is ambiguous, but the prediction is certain?

Also, ambiguity could be context sensitive? For e.g., the same thing can be
precise and ambiguous in multiple contexts?

---Vipul 






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Received on Monday, 18 June 2007 16:15:11 UTC