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Natural Deduction for First-Order Logic

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First-Order Logic SyntaxNatural Deduction for Propositional Logic+2 moreProof Strategies and Heuristics in Natural DeductionQuantifier Instantiation Rules in First-Order Proof Systems+1 more
natural-deduction quantifier-rules universal existential FOL-proof

Core Idea

Natural deduction for FOL extends propositional natural deduction with four quantifier rules. Universal introduction (∀I) derives ∀x φ(x) from φ(a) where a is an arbitrary fresh constant not mentioned elsewhere. Universal elimination (∀E) instantiates ∀x φ(x) to φ(t) for any term t. Existential introduction (∃I) derives ∃x φ(x) from φ(t). Existential elimination (∃E) discharges an assumption φ(a) when proving a conclusion that does not mention the fresh constant a. The freshness conditions on ∀I and ∃E are critical: they formalize the logical principle that reasoning about 'an arbitrary object' must not smuggle in extra assumptions.

How It's Best Learned

Prove simple theorems like ∀x P(x) → ∀x (P(x) ∨ Q(x)) in Fitch notation before attempting ∃-elimination. Pay close attention to which constants appear in the context when applying freshness conditions.

Common Misconceptions

Explainer

You already know natural deduction for propositional logic: every connective has an introduction rule (how to prove it) and an elimination rule (how to use it). FOL natural deduction extends this system by giving introduction and elimination rules for the two quantifiers ∀ and ∃. The rules look symmetric on the surface but have subtly different constraints that reflect a deep logical distinction: the difference between *an arbitrary object* and *a specific unknown object*.

Universal elimination (∀E) is the simple one: from ∀x φ(x), you can derive φ(t) for *any* term t you like. If everything has a property, then this specific thing has it. No freshness condition is needed — t can be anything, including terms that already appear in your proof. This is just instantiation. Universal introduction (∀I) is the inverse and is more constrained: to derive ∀x φ(x), you must have derived φ(a) where a is a fresh constant — one that doesn't appear in any undischarged assumption. The fresh constant represents a *generic* object: if you proved φ(a) without using any special property of a, then a stands for any object whatsoever, and you're entitled to universally generalize.

Existential introduction (∃I) is also unconstrained: from φ(t), derive ∃x φ(x). You have a witness, so something satisfies the property. Existential elimination (∃E) is the tricky rule. From ∃x φ(x) and a derivation of conclusion C from assumption φ(a) (where a is fresh), you may derive C. The idea: you don't know *which* object witnesses ∃x φ(x), so you name it a and reason from what you know about it (just that it satisfies φ). If you reach a conclusion C that doesn't mention a, then C holds regardless of which witness a actually is. The freshness condition on a is essential: if a appeared in your other assumptions or in C, your reasoning would smuggle in extra information about the witness, corrupting the inference.

A worked example cements the rules. Prove ∃x P(x) → ∃x (P(x) ∨ Q(x)). Assume ∃x P(x). Apply ∃E: assume P(a) for fresh a. By ∃I on P(a) ∨ Q(a) (derived via ∨I from P(a)), derive ∃x (P(x) ∨ Q(x)). This conclusion doesn't mention a, so ∃E discharges the assumption P(a) and gives ∃x (P(x) ∨ Q(x)) from ∃x P(x). The proof works because a serves as a stand-in for "whichever object witnesses the existential" — we don't need to know which one it is, only that it satisfies P. This four-rule extension of propositional natural deduction is complete for FOL: every valid first-order sentence has a natural deduction proof.

Practice Questions 5 questions

Prerequisite Chain

Understanding ZeroThe Number ZeroCounting to FiveCounting to 10Counting to 20Counting a Set of Objects Up to 20Cardinality: The Last Number CountedMatching Numerals to QuantitiesSubitizing Small QuantitiesAddition Within 10Number Bonds to 10Addition Within 20Doubles and Near DoublesDoubles Facts Within 10Near Doubles Facts Within 20Mental Math Strategies for AdditionMental Math: Adding and Subtracting TensAddition Within 100Repeated Addition as MultiplicationMultiplication as Equal GroupsMultiplication: ArraysBasic Multiplication Facts (0s, 1s, 2s, 5s, 10s)Multiplication Facts Within 100Division as Equal SharingDivision as Grouping (Measurement Division)Division: Grouping (Repeated Subtraction) ModelDivision: Fair Sharing ModelDivision as Equal SharingDivision as GroupingBasic Division FactsDivision Facts Within 100Multiplication and Division Fact FamiliesRelationship Between Multiplication and DivisionDivision Facts as Inverse of MultiplicationRemainders and Quotients in DivisionDivision Word ProblemsMulti-Step Word ProblemsSolving Multi-Step Word ProblemsMultiplication Word ProblemsDivision Word ProblemsIntroduction to Long DivisionFactors and MultiplesPrime and Composite NumbersEquivalent FractionsRelating Fractions and DecimalsDecimal Place ValueIntegers and the Number LineComparing and Ordering IntegersAbsolute ValueAdding IntegersSubtracting IntegersMultiplying IntegersIntroduction to ExponentsOrder of OperationsInteger Order of OperationsVariable ExpressionsThe Distributive PropertyVariables and Expressions ReviewIntroduction to PolynomialsAdding and Subtracting PolynomialsMultiplying PolynomialsFactorialPermutationsCombinationsCounting Principles: Addition and Multiplication RulesIntroduction to Graph TheoryPropositional Logic FoundationsLogical EquivalencesBoolean AlgebraIntroduction to Propositional LogicIntroduction to Predicate Logic (First-Order Logic)First-Order Logic SyntaxTerms and Atomic Formulas in FOLVariable Binding and ScopeSubstitution and UnificationNatural Deduction for First-Order Logic

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