User:IssaRice/Logical induction notation

From Machinelearning

This is in user space because it's not really about machine learning.

Term Notation Type Definition Notes
F-combination A S{0,1}Fn Function application of an F-combination uses square brackets instead of parentheses. Why? As far as I can tell, this is because each coefficient is in F so is itself a function. This means we have two senses of "application": we can pick out the specific coefficient we want (square brackets), or we can apply each coefficient to return something (parentheses).
Holdings from T against P¯ (a Q-combination) T(P¯) S{0,1}Q

Example of a 5-strategy given on p. 18 of the paper:

[(¬¬ϕ)*5ϕ*5](ϕϕ*5)+[ϕ*5(¬¬ϕ)*5](¬¬ϕ(¬¬ϕ)*5)

Since the coefficients are in F5, this is an F5-combination. Let's call this 5-strategy T5. We can pick out the coefficient for the ϕ term like T5[ϕ]=(¬¬ϕ)*5ϕ*5. But since each coefficient is a feature (which is a function), we can also apply each coefficient to some valuation sequence V¯, like this:

T5(V¯)=[(¬¬ϕ)*5(V¯)ϕ*5(V¯)](ϕϕ*5(V¯))+[ϕ*5(V¯)(¬¬ϕ)*5(V¯)](¬¬ϕ(¬¬ϕ)*5(V¯))

Now each coefficient is a real number, so T5(V¯) is an R-combination. Note that since T5:S{1}F5 is a function that takes a sentence or the number 1 and V¯ is a valuation sequence (not a sentence or number), there appears to be a type error in writing T5(V¯). What is going on is that we aren't evaluating T5 at V¯; rather, we are evaluating each coefficient of T5, to convert the range of T5 from F5 to R.

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