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Reasoning with Uncertain Information
An agent often has only uncertain information about its task and about its environment. The techniques I have described so far had limited abilities for representing and reasoning about uncertain knowledge. A statement such as P ∨ Q allows us to express uncertainty about which of P or Q is true, but I have not yet described how we might represent how certain we are about either P or Q.
In ordinary logic, we can deduce Q from P and P ⊃ Q. That is, if an agent knows P ⊃ Q, and it subsequently learns P, it can infer Q also. Are there analogous inference processes when information is uncertain? Various formalisms have been employed to represent and reason about uncertain information. I have already alluded to ...
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