Memra

Semantics: interpretation, model, satisfiable, valid

◈ 3 cards

Define an interpretation over a domain D and distinguish satisfiable / model / valid / inconsistent; apply the quantifier-negation equivalences (¬∀X P ≡ ∃X ¬P).

Giving symbols meaning

Syntax says which strings are legal; semantics says what they mean and whether they are true. A predicate calculus interpretation over a nonempty domain assigns:

  • each constant to an element of ;
  • each function of arity to a mapping ;
  • each predicate of arity to a mapping ;
  • each variable to a nonempty subset of (its allowable substitutions).

Given an interpretation, the truth value of any sentence is fixed by applying these mappings. Many different domains can satisfy the same set of sentences — a knowledge base is not tied to one world.

Four properties of a sentence (or set)

  • Satisfiable — there exists some interpretation (and variable assignment) that makes it true. Otherwise it is unsatisfiable.
  • Model — an interpretation that does make a sentence (or every sentence in a set ) true is a model of it. Formally, is a model of when every interpretation satisfying also satisfies — and then we say logically follows from .
  • Valid — true under every interpretation. A valid sentence is a tautology, e.g. . Validity is the predicate-calculus analogue of an all-true truth-table column.
  • Inconsistent — a set is inconsistent when no interpretation satisfies all of its members at once. It has no model.

These form a ladder of strength: valid satisfiable (a sentence true everywhere is certainly true somewhere), but not the reverse. p(a) is satisfiable (true in some worlds) yet not valid (false in others).

Worked example: classifying three sentences

Let the domain be people. (1) valid: in every interpretation, each object either has property or does not, so the disjunction is always true. (2) satisfiable but not valid: true in a world where someone likes ice cream, false in a world where no one does. (3) unsatisfiable (inconsistent): no interpretation can make a both have and not have , so the set has no model. Property (3) is the engine behind resolution refutation in Module 9: prove a goal by showing that negating it produces an inconsistent set.

Quantifier-negation equivalences

Pushing a negation across a quantifier flips the quantifier:

In words: "not everyone likes ice cream" () means "someone does not like ice cream" (). These are the quantifier analogue of De Morgan's laws and are needed when converting sentences toward clause form (Lesson 7).

resolveresolveempty clause — no modelp(a)in the KB¬p(a)negated goal
Why an inconsistent set is useful. The set <code>{p(a), ¬p(a)}</code> from the worked example has no model — no interpretation can make <code>a</code> both have and not have <em>p</em>. Read the figure bottom-up: assume the negation of what you want to prove, reach the empty clause, and the goal must follow. That is <strong>resolution refutation</strong>, the engine of Module 9.
negationequivalent toin words¬∀X P(X)∃X ¬P(X)not all ⟹ some do not¬∃X P(X)∀X ¬P(X)none ⟹ all do not¬∀X likes(X, ic) ≡ ∃X ¬likes(X, ic).
The quantifier analogue of De Morgan, and a required step when converting toward clause form (Lesson 7). In words: "not everyone likes ice cream" is not "everyone dislikes ice cream" — it is "someone does not".
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