Truth values, valuations, and evaluation of propositional formulas using truth tables.
Semantics assigns meaning to the formulas of propositional logic by assigning truth values to propositional variables and then extending this assignment to all formulas according to the logical connectives.
Truth Values
We use two truth values:
and:
The value means true, and the value means false, and every formula in classical propositional logic will receive exactly one of these two values once a valuation has been fixed.
Definition 1.10 (Valuation)
A valuation is a function:
from the set of propositional variables to the set of truth values.
Thus a valuation assigns to each propositional variable either or , and it should be understood as one possible assignment of truth values to the atomic statements of the language.
For example, if the variables are , , and , then one possible valuation is given by:
Definition 1.11 (Evaluation of Formulas)
Every valuation extends uniquely to a function on all formulas, also denoted by , by recursion on the structure of formulas.
If is a propositional variable, then is the value already assigned to by the valuation.
If , then:
if and only if:
If , then:
if and only if:
If , then:
if and only if:
If , then:
if and only if:
If , then:
if and only if:
This recursive definition is possible because formulas were defined inductively, and it gives a precise way to compute the truth value of any formula from the truth values of its variables.
Example 1.12
Let be the valuation defined by:
Then:
because is true under , and negation reverses the truth value.
Also:
because a conjunction is true only when both conjuncts are true.
We have:
because a disjunction is true when at least one disjunct is true.
Finally:
because implication is false exactly when its antecedent is true and its consequent is false.
Truth Tables
A truth table records the value of a formula under all possible valuations of the variables that occur in it.
If a formula contains distinct variables, then there are:
possible assignments of truth values to those variables, and therefore the truth table has rows.
Truth tables are useful because they give a complete semantic description of a formula in a finite and explicit form, at least when the number of variables is small enough to make the table manageable.
Example 1.13
Consider the formula:
The truth table is:
The last column is in every row, so the formula is true under every valuation.
Definition 1.14 (Satisfiability, Validity, Contradiction)
A formula is satisfiable if there exists a valuation such that:
A formula is valid if for every valuation :
A formula is a contradiction if for every valuation :
These three notions classify formulas according to their behavior across all possible valuations.
Example 1.15
The formula:
is valid, because for every valuation either is true or is false, and in both cases the disjunction is true.
The formula:
is a contradiction, because no valuation can make both and true at the same time.
The formula:
is satisfiable but not valid, because it is true when both and are true, but it is false under many other valuations.
Lemma 1.16 (Unique Evaluation)
For every valuation and every formula , the truth value is uniquely determined.
Proof
The proof is by structural induction on the formula .
If is a propositional variable, then is uniquely determined by the definition of the valuation.
If , then by the induction hypothesis the value is uniquely determined, and therefore the value of is uniquely determined by the truth rule for negation.
If for a binary connective , then by the induction hypothesis the values and are uniquely determined, and therefore the value of is uniquely determined by the truth rule for the connective .
Boolean Function View
If a formula contains variables among:
then determines a Boolean function:
This function sends each tuple of truth values assigned to the variables to the truth value of the formula under the corresponding valuation.
This viewpoint is useful because it connects propositional logic with Boolean algebra, digital circuits, and computation, where formulas can be studied as functions from binary inputs to binary outputs.