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semantics of the language Propf is given by assigning ttruth values to
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t each proposition in Prop. Clearly, an arbitrary assignment of truth values is
You should very carefully inspect everything is critical that with the meaning
not interesting, since we would likethis table! Itto be consistentyou memorize
17 X in the set {∧, ∨, ⊕, →, ↔} a binary function MX : B × B → B. The truth
tables of these connectives are as follows:
P
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t Semantics Q M∧ (P, Q) M∨ (P, Q) M⊕ (P, Q) M→ (P, Q) M↔ (P, Q)
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t You should very carefully inspect this table! It is critical that you memorize
and fully understand the meaning of each connective.
The semantics of the language Prop is given by assigning truth values to
each proposition in Prop. Clearly, an arbitrary assignment of truth values is
not interesting, since we would like everything to be consistent with the meaning
of the connectives that we have just learned. For example, if the propositions a
and b have been assigned the value t, then it is reasonable to insist that a ∧ b
be assigned the value t as well. Therefore, we will introduce the concept of a
valuation, which models the semantics of Prop in an appropriate way.
A valuation v : Prop → B is a function that assigns a truth value to each
proposition in Prop such that
V1. v ¬a = M¬ (v a)
V2. v (a ∧ b) = M∧ (v a , v b)
V3. v (a ∨ b) = M∨ (v a , v b)
V4. v (a ⊕ b) = M⊕ (v a , v b)
V5. v (a → b) = M→ (v a , v b)
V6. v (a ↔ b) = M↔ (v a , v b)
holds for all propositions a and b in 18
Prop. The properties V1–V6 ensure and fully understand the meaning of each connective.
The semantics of the language Prop is given by assigning truth values to
each proposition in Prop. Clearly, an arbitrary assignment of truth values is
not interesting, since we would like everything to be consistent with the meaning
of the connectives that we have just learned. For example, if the propositions a
and b have been assigned the value t, then it is reasonable to insist that a ∧ b
be assigned the value t as well. Therefore, we will introduce the concept of a
valuation, which models the semantics of Prop in an appropriate way.
A valuation v : Prop → B is a function that assigns a truth value to each
proposition in Prop such that Valuations V1.
V2.
V3.
V4.
V5.
V6. v ¬a = M¬ (v a)
v (a ∧ b) = M∧ (v a , v b)
v (a ∨ b) = M∨ (v a , v b)
v (a ⊕ b) = M⊕ (v a , v b)
v (a → b) = M→ (v a , v b)
v (a ↔ b) = M↔ (v a , v b) holds for all propositions a and b in Prop. The properties V1–V6 ensure
that the valuation respects the meaning of the connectives. We can restrict a
valuation v to a subset of the set of proposition. If A and B are subsets of
Prop such that A ⊆ B...
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This note was uploaded on 03/24/2014 for the course CSCE 222 taught by Professor Math during the Fall '11 term at Texas A&M.
 Fall '11
 math

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