I now proceed to present a series of results whose overall goal is to make the handling of formal proofs more efficient and natural. These results formalize different methods of reasoning commonly used in practice. A second goal in presenting these results is in preparing the way for the proof of the completeness theorem.
Theorem 7 (The deduction theorem) If
is a set of formulas, and
and
are formulas, then
if and only if
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Proof: One direction is easy: Given any proof witnessing one can extend it with
and the resulting sequence witnesses
We are allowed to add
since it is in
and we can then add
by MP.
The other direction requires a bit more work. We actually present a procedure that transforms a proof witnessing say
into a proof witnessing
There are three cases for each
in the sequence:
Case 1: is either an axiom or
Replace
with the sequence
and notice that this is a proof from
of
We will frequently use this argument in what follows.
Case 2: Replace
with the proof of
given in Example 9 from last lecture.
Case 3: comes from previous
by MP. Say
The procedure has so far provided us with a sequence
that contains a proof of
from
and also a proof of
from
Replace
with the sequence
and notice that
is a proof of
from
Definition 8 A set
of formulas is formally inconsistent iff there is some formula
such that
and
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Just as in the case of the tree system, an inconsistent set of axioms can prove anything.
Fact 1 If
is formally inconsistent, then
for all
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Proof: Let be such that
Since
the argument of Case 1 from Theorem 7 gives us that
Similarly, since
then
Invoking axiom (3) and using MP twice, we are done.
Theorem 9 (Proof by contradiction)
is formally inconsistent iff
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Proof: One direction is clear: If then
To prove the converse, we need a lemma:
Lemma 10
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Proof: Use axiom (3) in the form Since
is given, we then have that
We also have a proof of
Using MP twice, we conclude
Suppose now that is formally inconsistent, say
Since
then
By the deduction theorem,
Using an appropriate instance of axiom (3) and invoking MP twice, we obtain that
as required.
Remark 3 Conversely,
To see this, simply use proof by contradiction, noticing that
is formally inconsistent.
Remark 4 It is in order to obtain Theorem 9 that we stated axiom
the way we did. Another natural axiom to consider would have been
The system one obtains from adopting axioms
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and
is strictly weaker (in several senses; for example, it proves fewer theorems) that the system we are using.
The standard system of propositional intuitionistic logic is obtained by adopting axioms
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and
In this system, one can prove that
but not that
The semantics of propositional logic (to be discussed below) is also considerably simpler than the appropriate semantics of its intuitionistic counterpart.
Theorem 11 (Proof by contrapositive)
iff
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Proof: By symmetry, it is enough to prove the left-to-right implication. Assume Then
is formally inconsistent. By proof by contradiction,
Say that is formally consistent precisely when it is not formally inconsistent. It should be clear by now that the main question we need to address is whether there are formally consistent sets
We will soon show this, but for now we remark that in order to obtain many examples of such sets
it is enough to see that
(i.e., just the set of axioms) is formally consistent.
Lemma 12 Suppose that
is formally consistent. Then, for any formula
either
or
is also formally consistent.
Proof: Otherwise, both and
are formally inconsistent. By proof by contradiction, it then follows that
and therefore
itself is formally inconsistent.
Say that a set is complete iff for any formula
either
or
The argument below should remind the reader of (part of) the argument of completeness for the tree system.
Corollary 13 Suppose that
is formally consistent. Then there is a set
that is both formally consistent and complete.
Proof: First notice that by an easy counting argument there are only countably many formulas, so one can enumerate them as Now use Lemma 12 to form a sequence
where each
is formally consistent and either
or
Set and note that
extends
and is both formally consistent and complete, as required.
9. Semantics of propositional logic
We now proceed to assign an interpretation to our axioms and rules of deduction. The idea is that we decide “arbitrarily” precisely which propositional variables represent true statements, and from there we can conclude the truth or falsity of any formula. This will allow us, among other things, to verify that there are formally consistent sets
Definition 14 A truth assignment or valuation is a function
from the set of propositional variables into
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We identify with false and
with true, so
is our formalization of the statement that
is true.
Definition 15 The lifting of a valuation
is the function
extending
defined on the set of all formulas, and given recursively by the following clauses:
The common practice (that we follow) is to just write instead of
unless there is danger of confusion. Note that
for all formulas
and that
iff
and
(This should probably remind the reader of truth tables.)
There is a slight inconvenience with this definition, in that even if a formula only uses one propositional variable
we need to consider functions defined on infinitely many arguments in order to evaluate the truth or falsity of
The following straightforward observation allows us to avoid this problem.
Definition 16 The support
of a formula
is the set of propositional variables mentioned in
Recursively, one can define this set by the following clauses:
The following can be easily shown by induction on the length of a parsing sequence.
Fact 2 Let
be a formula. Suppose that
and
are valuations, and that
Then in fact
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Remark 5 Going through the parsing sequence of a formula provides us with an easy algorithm to evaluate
from
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Recall our convention that is shorthand for
Given a valuation
we then have
and it follows that
iff
Similarly, one can check that iff
and that
iff
Our conventions where chosen so that we would recover the usual truth tables of the connectives.
Definition 17 Given a valuation
and a formula
say that
, “
models
,” or “
satisfies
,” or “
makes
true,” iff
Otherwise, we write
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Remark 6 We can easily check that:
iff
iff
and
iff
or
iff either
or else
iff (
iff
). I.e., iff either both
and
or else both
and
Definition 18 A formula
is said to be valid, or a tautology, iff
for all valuations
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There are many valuations, but thanks to Fact 2, only finitely many (
) valuations need to be considered to determine whether
is a tautology or not.
The following are examples of tautologies:
Example 10 The axioms are tautologies. For example, consider
Let
be a valuation. Then
iff
and
i.e., iff
and
and
which of course is impossible.
Similar easy contradictions hold in the other two cases:
iff
and
iff
and
but
This last clause requires that
and
The second to last clause requires then that
Hence,
but
so
against our assumption.
Finally,
iff
and
and
This last clause forces that
and therefore we must have both
and
which is impossible.
Example 11
is a tautology. Whenever
is a tautology, we say that
and
are logically equivalent,
One also says that
and
are semantically indistinguishable. It is straightforward to verify that
is an equivalence relation.
Example 12
is a tautology. This is easily verified directly. Next lecture we will see that, in fact, any theorem (i.e., any
such that
) is a tautology.
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