Introduction
Class notes
Predicate Logic
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Chapter 1 Propositional Logic
1.1 Introduction
1.1.1 What is a proof ?
Définition 1
A proof is a piece of text written by a human to convince another
human that some fact is true.
Problem 1
[, p. 2]
You have been selected to serve on jury duty for a criminal case.
The attorney for the defense argues as follow:
``If my client is guilty, then the knife was in the drawer. Either
the knife was not in the drawer, or Jason Pritchard saw the knife.
If the knife was not there on October 10, it follows that Jason Pritchard
did not see the knife. Furthermore, if the knife was there on October
10, then the knife was in the drawer and also the hammer was in the
barn. But we all know that the hammer was not in the barn. Therefore,
ladies and gentlemen of the jury, my client is innocent.''
Are you convinced ?
Problems:

What is the goal ?
 What are the hypothesis ?
 What is the logical link between the statements ?
 There is plenty of unrelevant information.
A good proof consists of:

A description of the goal
 Hypothesis
 Statements, one after the other.
Each one derives logically from the previous ones.
 Conclusion
Let's look at a very simple example:
Théorème 1
Let x and y be two integers.
If x is odd and y is odd, then xy is odd.
Proof.
Assume x is odd and y is odd.
Let k be an integer such that x=2k+1.
Let l be an integer such that y=2l+1.
Then, xy=(2k+1)(2l+1)=2(2kl+k+l)+1.
Note that 2kl+k+l is an integer.
Conclusion: xy is odd.
1.1.2 Formal and Informal proofs
What do we mean by ``derives logically from the previous ones''
?
What operations shall we consider as legal ?
To learn more about this, we need a model of what we intuitively
consider as true, or logic.
This model we are going to construct is called formal logic.
1.1.2.1 Formal systems
Définition 2
A formal system
is build by providing:

a set of strings: the axioms
 a set of rewriting rules
A string that can be obtained from the axioms by applying rewriting
rules is called a theorem
of the formal system.
The proof
of a theorem is a description of the axioms and rules
used to get the theorem.
The set of all theorems is called the language
defined by the
formal system.
Exemple 1
The MIU formal system[]
A formal system does not need to have any meaning or semantic.
It's pure syntax.
We will build formal logic as a formal system, with a meaning!

The strings will be logic formulas
 The axioms will be simple logic formulas that we interpret intuitively
true
 The rewriting rules will be transformations we interpret intuitively
as valid
Then, any theorem of this formal system shall be interpreted as true.
We will have to be very careful with the choice of the axioms and
rules!
1.1.2.2 Proofs and programming
Writing a proof and a writing a program are very similar:
Proofs 
Programming 
Purpose 
Theorem 
Function prototype 
How to use it 
Proof 
Function definition 
How it works 
Intuitive proof 
Comments 
Explanation for the reader 
Informal proof 
Program in a high level language 
Human readable 
Formal proof 
Program in assembly language 
Machine readable 
Checking an informal proof 
Compiling 
Human readable > Machine readable 
This comparison is not gratuitous. There are deep links between proofs
and programming which have been studied a lot in the last decades.
This is called the CurryHoward correspondence.
1.2 Statements, Symbolic Representation, and Tautologies
As a first step, let's define logic formulas and their interpretation.
1.2.1 Statements and Propositions
Définition 3
A statement (or proposition) is a sentence which is
either true or false.
Exemple 2
Which sentences below are statements ?

The sky is cloudy
 It's raining
 Are you happy ?
 He is happy
 Three divides five
 There are life forms on other planets in the universe
Notation 1
A, B, C: symbols representing a statement.
Each of those symbols can be given a truth value, either True (T for
short) or False (F for short).
1 is a statement if truth value True.
0 is a statement if truth value False.
1.2.2 Connectives
How can we combine two statements ?
1.2.2.1 And (conjunction), or (disjunction)
Exemple 3
``The sky is cloudy'': A. ``It's raining'': B.

``The sky is cloudy AND it's raining'': A/\ B
 ``The sky is cloudy OR it's raining'': A\/ B
Définition 4
The truth table
of a formula describes when it's true or not,
given the truth value of the symbols.
A 
B 
A/\ B 
A\/ B 
T 
T 


T 
F 


F 
T 


F 
F 


1.2.2.2 Exclusive or
Exemple 4
``Cheese or desert''
You get cheese: A
You get desert: B
Définition 5
A exclusive or B: A xor B.
Truth table:
A 
B 
A xor B 
T 
T 

T 
F 

F 
T 

F 
F 

1.2.2.3 Implication
Exemple 5
``If I get my driver license, I will open a bottle of champagne''.
``I get my driver license'': A.
``I open a bottle of champagne'': B.
Définition 6
A implies
B: A> B.
Truth table:
A 
B 
A> B 
T 
T 

T 
F 

F 
T 

F 
F 

Why this should be true:

no real meaning but we have to pickup one to make it easy
 Most reasonable is true
Why this should be false:
This one can be tricky. To help you make up your mind, here are some
examples:

If I don't get my driver license, but still I open a bottle of champagne,
am I a liar?
 ``If I open a bottle of champagne, I will get my driver license''
 ``When pig flies, I'll give you 2 billions dollars''
Well, as strange as it can sound, F> T is a true formula.
If you start from an utterly false hypothesis, you can prove anything.
``Avec des si, on pourrait mettre Paris en bouteille''
``With ifs, Paris could be put in a bottle''
Remarque 1
A> B and B> A are not the same!
Sounds stupid ?
Look carefully around you! This is the most common logic error in
peoples argumentations.
And it's not always an involuntary error.
Exercice 1
Give the antecedent and the consequent in the following sentences

If the rain continues, then the river will flood
 A sufficient condition for network failure is that the central switch
goes down
 It's raining only if there are clouds in the sky
 It's raining if there are clouds in the sky
 It's raining if and only if there are clouds in the sky
 The avocados are ripe only if they are dark and soft
 A good diet is a necessary condition for a healthy cat
1.2.2.4 Equivalence
Exemple 6
The knight will win if and only if his armor is strong
The knight will win: A.
His armor is strong: B.
This sentence contains two informations:

The knight will win if his armor is strong: A< B.
 The knight will win only if his armor is strong: A> B.
Définition 7
A is equivalent to
B: A<> B.
Truth table:
A 
B 
A<> B 
T 
T 

T 
F 

F 
T 

F 
F 

1.2.2.5 Not
So far we defined binary connectives, that is connectives which took
two arguments.
Here is now a unary connective, taking just one argument.
Exemple 7
It will not rain tomorrow
The knight will win: A.
His armor is strong: B.
This sentence contains two informations:

The knight will win if his armor is strong: A< B.
 The knight will win only if his armor is strong: A> B.
Définition 8
not A: A' (more usual notation: ¬ A)
Truth table:
1.2.3 Complex Well Formed Formulas
Définition 9
A formula
is a string of

symbols: A, B, ...
 connectives: \/, /\, >, < , '
, ...
 parenthesis: (, ), [, ]
A well formed formula
(or wff) is a formula which satisfies
certain syntax rules.
Notation 2
Symbols representing wff: P, Q, R.
1.2.3.1 Order of precedence
The formula A/\ B> C' is ambiguous. It can be read
as:

(A/\ B)>(C'),
 A/\[B>(C')],
 [(A/\ B)> C]'
Solution 1: always put all parenthesis (not very readable).
Solution 2: put an order of precedence between the operators:

Connectives within parentheses, innermost parenthesis first
 '
 /\, \/
 >, <
 <>
With this order of preference, A/\ B> C' unambiguously
refer to (A/\ B)>(C)'.
1.2.3.2 Evaluation of a wff
From the truth values of the basic statements, and the elementary
truth tables, one can evaluate the truth value of a wff.
Exemple 8
A/\ B> C', with A true, B false and C true:
A/\ B: false
C': false
A/\ B> C': true
There is a recursive algorithm to compute the evaluation of a wff.
1.2.3.3 Truth table of a wff
This yields an algorithm for computing the truth table of a wff.
A 
B 
C 
A/\ B 
C' 
(A/\ B)>(C') 
T 
T 
T 



T 
T 
F 



T 
F 
T 



T 
F 
F 



F 
T 
T 



F 
T 
F 



F 
F 
T 



F 
F 
F 



Problem 3
What's the size of a truth table?
Problem 4
Can any truth table be obtained by a wff?
1.2.4 Tautologies and Contradictions
Définition 10
A tautology is a statement that is always true.
A contradiction is a statement that is always false.
Exemple 9
A\/ A'
``Today the sun shine or today the sun does not shine''.
Exercice 2
Are the following wff tautologies or contradictions ?

A/\ A'
 A<> A
 (A/\ B)<>(B/\ A)
 (A/\ B)> A
Algorithm to check for a tautology?
Compute the truth table!
It's slow (2^{n}, where n is the number of propositions), but
it works.
For certain simple forms of propositions, there is a much faster algorithm
(see [, Tautology test, p. 13]).
Exemple 10
Is [(A/\ B> C')/\(E< D)]<>[(E< D)/\(A/\ B> C')]
a tautology ?
Let P:=(A/\ B> C') and Q:=(E< D).
The formula above is [P/\ Q]<>[Q/\ P].
Let's prove it's a tautology.
Take some truth values for A, B, C, D, E.
P and Q will then have some truth value.
But we know that (A/\ B)<>(B/\ A) is a tautology.
So [P/\ Q]<>[Q/\ P] will be true!
We don't actually need to compute the truth table of P and Q.
Remarque 2
Whenever you have some tautology, if you replace ALL occurrences of
some basic statement (say A) by a more complicated wff, you still
get a tautology.
1.2.5 Equivalence of wff
Let P and Q be two wff, and suppose P<> Q is
a tautology.
Then P and Q have the same truth table.
Définition 11
P and Q are equivalent (noted P <=> Q) if they have
the same truth table.
Remarque 3
Writing P<> Q or P <=> Q is different.
In the first case, you just represent a formula, which can be true
or false.
In the second case, you claim that the wff P<> Q is
a tautology.
1.2.5.1 Basic equivalent wff
What is the negation of ``Peter is tall and thin'' ?
Identity (id) 
A\/0 <=> A 

A/\1 <=> A 
Complement (comp) 
A\/ A' <=> 1 

A/\ A' <=> 0 
Commutativity (comm) 
A\/ B <=> B\/ A 

A/\ B <=> B/\ A 
Associativity (ass) 
(A\/ B)\/ C <=> A\/(B\/ C) <=> A\/ B\/ C 

(A/\ B)/\ C <=> A/\(B/\ C) <=> A/\ B/\ C 
Distributivity (dist) 
A\/(B/\ C) <=> (A\/ B)/\(A\/ C) 

A/\(B\/ C) <=> (A/\ B)\/(A/\ C) 
Double negation (dn) 
A'' <=> A 
De Morgan's Law (dm) 
(A\/ B)' <=> A'/\ B' 

(A/\ B)' <=> A'\/ B' 
Implication (imp) 
A'\/ B <=> A> B 
Remarque 4
Notice the duality between \/ and /\.
Unlike + and · they play a perfectly symmetric role in all
formulas.
1.2.5.2 More equivalent wff using substitution
Exemple 11
(A/\ B)/\1 <=> (A/\ B).
Remarque 5
Let P and Q be equivalent wff.
If you replace all occurrences of some basic statement by another
wff, you still get two equivalent wff's.
Exemple 12
A/\(B\/ C) <=> A/\(C\/ B)
Remarque 6
Let P and Q be equivalent wff.
If P appears exactly as a subformula of a bigger wff, then
you can substitute P by Q and get an equivalent wff.
1.2.5.3 What's the point ?
Rewriting a formula to simplify it:
Exercice 3
[, Example 7 p.12]

If ((outflow > inflow) and not ((outflow>inflow) and (pressure < 1000)))
Do something;
Else
Do something else;
EndIf
Write the wwf corresponding to the test.
Rewrite this wwf using equivalence rules.
Electronic circuits and logical gates:
Exercice 4
Build an electronic circuit for (A/\ B)> C'.

Case 1: you have electronic gates TRUE, FALSE, AND, OR, NAND.
 Case 2: you only have electronic gates NAND.
1.3 Propositional logic
We have seen propositions, well formed formula for formalizing statements.
We now need to formalize arguments.
Exemple 13
[, Example 17 p. 28]
Let's formalize the following argument:
``If interest rates drop, the housing market will improve.
Either the federal discount rate will drop, or the housing market
will not improve.
Interest rates will drop.
Therefore the federal discount rate will drop.''
Basic statements:

I: Interest rates drop
 H: The housing market will improve
 F: The federal discount rate will drop
Argument: (I> H)/\(F\/ H')/\ I > F
Définition 12
An argument is a wff of the form P_{1}/\ P_{2}/\···/\ P_{n} > Q.
P_{1},···,P_{n} are the hypothesis.
Q is the conclusion.
The argument is valid iff P_{1}/\ P_{2}/\···/\ P_{n} > Q
is a tautology.
Exercice 5
Prove that the following arguments are valid:

[A>(B> C)] > [(A/\ B)> C]
 [(A/\ B)> C] > [A>(B> C)]
Why is this reasonable ?
``If the sun shine then if you don't put sun cream, you will get
burned'': A > (B> C)
``If the sun shine and you don't put sun cream, then you will get
burned'': (A/\ B) > C
Exemple 14
``George Washington was the first president of the United States.
Therefore everyday has 24 hours.''
We put some more restrictions to only keep ``meaningful'' arguments.

Q has some relation with the P_{i}.
 the P_{i} are not in contradiction
1.3.2 Proof sequences
So now, how to prove that an argument is a tautology ?

Use the truth table
 Use formal logic!
Exemple 15
Let's prove that the argument A\/(A\/ B)' > (A\/ B') is
valid.
We are lazy to compute the truth table.
Instead, we assume that the hypothesis is valid, and use a series
of equivalences to deduce that the conclusion is valid.

1. 
A\/(A\/ B)' 
(Hypothesis) 
2. 
A\/(A'/\ B') 
(De Morgan's, 1) 
3. 
(A\/ A')/\(A\/ B') 
(Distributivity, 2) 
4. 
1/\(A\/ B') 
(Complement, 3) 
5. 
(A\/ B') 
(Identity, 4) 

What we just did is called a proof sequence.
This is our first proof using formal logic.
Exercice 6
Prove that the following argument is valid:
(A\/ B)'\/(A'/\ B) > A'
Définition 13
Formal Logic: wff + set of derivation rules (formal system).
What derivation rules shall we accept?
We want our formal logic to be:

Correct
 Complete
 Minimal
 Powerful
1.3.3 Looking for derivation Rules
Exemple 16
A/\ B > A
Equivalences rules are not enough.
We can't prove the previous statement, because A/\ B is strictly
stronger than A.
We have build equivalence rules from equivalences P<> Q.
We can build Inference rules from any valid argument P> Q.
Rule name 
From 
Can derive 
modus ponens (mp) 
P, (P> Q) 
Q 
modus tollens (mt) 
(P> Q), Q' 
P' 
conjunction (con) 
P, Q 
P/\ Q 
simplification (sim) 
P/\ Q 
P, Q 
addition (add) 
P 
P\/ Q 
Exemple 17
A/\(A> B)/\(B> C) > C

1. 
A/\(A> B)/\(B> C) 
(Hypothesis) 
2. 
A 
(Simplification, 1) 
3. 
A> B 
(Simplification, 1) 
4. 
B 
(Modus ponens, 2, 3) 
5. 
B> C 
(Simplification, 1) 
6. 
C 
(Modus ponens, 4, 5) 

Exemple 18
(A>(B\/ C))/\ B'/\ C' > A'

1. 
(A>(B\/ C))/\ B'/\ C' 
(Hypothesis) 
2. 
(A>(B\/ C)) 
(Simplification 1) 
3. 
(B'/\ C') 
(Simplification 1) 
4. 
(B\/ C)' 
(De Morgan's 3) 
5. 
A' 
(Modus tollens 4, 5) 

Exercice 7
Prove the validity of the following arguments using formal logic:

A/\(B> C)/\[(A/\ B)>(D\/ C')]/\ B> D
 A'/\(A\/ B)> B
 A'/\ B/\[B>(A\/ C)]> C
 A/\ A'> B
Theorem 1
This formal logic is correct and complete.
The correctness of the formal logic comes from the way we built the
rules from valid arguments.
Proving it's complete is far more difficult.
1.3.4 Methods to make it easier
Our logic is complete, but still not very practical to use.
Here are some tricks to make it easier.
Most of the time, the proofs start like this:

1. 
(A>(B\/ C))/\ B'/\ C' 
(hyp) 
2. 
(A>(B\/ C)) 
(Simp 1) 
3. 
(B'/\ C') 
(Simp 1) 
··· 
··· 
··· 

The steps 2 and 3 are pretty trivial, and it's reasonable to start
directly with:

1. 
(A>(B\/ C)) 
(hyp) 
2. 
(B'/\ C') 
(hyp) 
··· 
··· 
··· 

1.3.4.1 The deduction method
Exemple 19
(A> B)/\(B> C) > (A> C)
The obvious start is:

1. 
(A> B) 
(hyp) 
2. 
(B> C) 
(hyp) 

But then it's pretty painful:

3. 
A'\/ B 
(imp 1) 
4. 
A'\/(B> C) 
(add 2) 
5. 
(A'\/ B)/\(A'\/(B> C)) 
(con 3, 4) 
6. 
A'\/(B/\(B'> C)) 
(dist 5) 
7. 
A'\/ C 
(mp 6) 
8. 
A> C 
(imp 7) 

Here it's easier to first rewrite the argument into an equivalent
argument.
We have seen that P>(Q> R) and (P/\ Q)> R
are equivalent.
So we can prove A/\(A> B)/\(B> C) > C
instead, which is straightforward:

1. 
A 
(hyp) 
1. 
(A> B) 
(hyp) 
2. 
(B> C) 
(hyp) 
3. 
B 
(mt 1, 3) 
4. 
C 
(mt 2, 4) 

This trick is called the deduction method.
It's powerful because we have:

a simpler goal
 more hypothesis
Exercice 8
(A> B)/\[B>(C> D)]/\[A>(B> C)] > (A> D)
1.3.4.2 Additional deduction rules
As we have seen, any valid argument could be transformed into a new
rule.
Exemple 20
Here are two useful rules.
Rule name 
From 
Can derive 
hypothetical syllogism (hs) 
P> Q, Q> R 
P> R 
contraposition 
P> Q 
Q'> P' 
Adding those new rules won't change the power of the formal logic,
but can make it more convenient. On the other hand, a minimal formal
logic is nice since it's less error prone, and it's easier to remember
all the rules.
It's up to you to choose which rules you want to use (and learn).
Exemple 21
(P> Q)/\(P'> Q)> Q.
1.4 Verbal arguments
We can now start checking verbal arguments.
Exemple 22
Let's prove the following verbal argument[, Example 17 p. 28]:
``If interest rates drop, the housing market will improve.
Either the federal discount rate will drop, or the housing market
will not improve.
Interest rates will drop.
Therefore the federal discount rate will drop.''
Exercice 9
Prove the following verbal argument[, Ex. 30 p. 32]:
``If the program is efficient, it executes quickly.
Either the program is efficient or it has a bug.
However, the program does not execute quickly.
Therefore it has a bug.''
1.5 Summary
1.5.1 Different levels of logic
Three levels for arguments:

formal argument as a string of symbols, proof sequence (syntactic
level).
 formal argument as a truth table (semantic level).
 verbal argument (interpretation level).
Any verbal argument based on propositions can be translated into a
formal argument.
The propositional logic system is complete and correct:

Any formal argument proved syntactically is valid semantically.
 Any semantically valid formal argument can be proved syntactically
(it can be hard, though!).
1.5.2 Syntactic proof versus semantic proof
Testing an argument by computing it's truth table is purely mechanical.
So, what's the point of formal logic ?

It's often faster and shorter to write
 You have more chance to grab the meaning of an argument
 In predicate logic we won't be able to rely on truth tables
Introduction
Class notes
Predicate Logic
Propositional Logic /
CSM MACS358 /
Nicolas M. Thiéry
Last modified: Fri Jan 19 13:12:15 2007