- From: Paulo CG Costa <pcosta@gmu.edu>
- Date: Mon, 18 Jun 2007 01:23:10 -0300
- To: public-xg-urw3@w3.org
Hello Giorgos, Vipul, and MItch, Please, find my comments embedded. On Jun 15, 2007, at 5:01 AM, Giorgos Stoilos wrote: > ________________________________________ >> From: public-xg-urw3-request@w3.org [mailto:public-xg-urw3- >> request@w3.org] >> On Behalf Of Paulo CG Costa >> Sent: Thursday, June 14, 2007 12:59 PM >> To: public-xg-urw3@w3.org >> Subject: Model and sources of uncertainty >> >> Dear Mitch, >> >> The model on types of uncertainty lists only three of them: >> 1 - Vagueness >> 2 - Randomness >> 3 - Ambiguity >> >> How about: >> - unreability: knowledge from a source that is not 100% trustfull, >> - dissonance: we see the same piece of information, but each have a >> distinct interpretation, >> - incompleteness: which is not vagueness, since you can have a >> clear view >> of just part of the information, >> - inconclusiveness: we have clear, deterministic, non ambiguous >> information, which is also complete, we both agree upon it, and >> the source >> is reliable, but it is not enough to come up with any conclusive >> assertion. > > I am a bit confused about some of these. How does ambiguity differ > from > dissonance? 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. 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. > In the definition of inconclusiveness you use the term "not > enough" (i.e. incomplete). Thus, is it related to incompleteness? If you have complete information about an inherently probabilistic phenomena (thinking on Quantum theory might help here) then you still can't reach a uncertainty-free conclusion. > Some examples might also help. Please, be aware that when it comes to devising good examples I am just pathetic. Contradictory evidence: - Every computer in the product design department is a mac. - Mary works in a Dell computer from the product design department. Conflicting evidence: - People form the design department voted Mary, a brilliant software designer, for employee of the year. - John, the design department's leader, blamed Mary for the poor quality ratings the department got this year. Ambiguous evidence: - Sam and Max were seen in the woods, they are hunting dogs (ambiguity in the meaning - patent ambiguity) - Only tall people can play Basketball (What is a tall person - lack of precision - latent ambiguity) > BTW, I would also add "inconsistent" in the list; where in the same > knowledge base there exist contradictory axioms. An inconsistent KB is the result of contradictory evidence, which is a special kind of dissonant evidence. All in all, I have a slight different view with respect to Mitch's ontology. 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. Therefore, the only possible types of uncertainty (generally speaking) are: Epistemic - due to imperfect knowledge Essential - due to phenomena that is intrinsically randomic How to differentiate? Maybe a modified version of the Clairvoyant test: Suppose one has the ability to know everything about anything, and you ask her about the outcome of a given phenomena. Would she be able to predict it? If yes, then we are talking about epistemic uncertainty. Else, we are talking about intrinsic (or any similar word) uncertainty. Further, I'd list the possible causes (sources) that might lead to such situation: 1 - You have evidence that is (are): Inconclusive (see above) Ambiguous (see above) --> one cause of ambiguous evidence is vagueness. Dissonant (see above) --> encompasses contradictory and conflicting evidence Incomplete Unreliable 2 - You have an essentially random event. That is, ambiguity (for example) is not a type of uncertainty, but a source of uncertainty. An ambiguous statement or axiom will have many possible interpretations, and will thus prevent one to make inferences on the basis of that statement. Anyway, the above is just an initial view that might help with the discussion. All the best, Paulo
Received on Monday, 18 June 2007 04:23:28 UTC