In constructive logic, a proof is an evidence about the truth of a proposition, in probability theory, we also have evidences, just the evidence are not decisive, but only changing we degree of belief of the proposition.
We need a calculus of evidences.
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Is Bayes networks a calculus of evidences?
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We might observe more
{ A: ..., B: ... }
or{ A: ... }
.If we view evidence as observing more and more objects, what is the form of direct evidence of a conditional proposition
B -> A
, which increaseP(A | B)
?Is
B
merely a space for indexing, and evidence ofA
is evidence of a dependent type? -
Think about Polya's book, it seems has more complicate evidences.
If we are not sure about
A
, but we have proof ofA -> B
and proof ofB
, are't these proofs evidence ofA
?The above inference is an abduction, so evidence with uncertainty is constructed by abduction and induction?
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A database of evidences.
- Like the PLANNER language?
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It seems logic is the key, which can connect many domain of study.
- type theory.
- probability.
- computation -- SAT solver.