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Truth Functions and Interpretation

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Propositional ConnectivesPropositional Semantics and Valuations→→Formula Evaluation and Truth Tables
propositional-logic semantics truth-functions

Core Idea

In propositional logic, each connective (AND, OR, NOT, IMPLIES) defines a truth function that determines the truth value of a complex formula based on the truth values of its parts. An interpretation assigns truth values to atomic propositions, and these combine via truth functions to determine the truth value of any formula.

How It's Best Learned

Start with small formulas like (A ∧ B) and work through how their truth values depend on A and B. Visualize truth functions with simple diagrams before moving to complex nested formulas.

Common Misconceptions

Explainer

You already know the connectives AND (∧), OR (∨), NOT (¬), and IMPLIES (→) from propositional logic, and you know that propositions have truth values. A truth function makes this precise: it is a function from tuples of truth values to a truth value. Conjunction (∧) is a function f: {T, F} × {T, F} → {T, F} that maps (T,T) to T and everything else to F. This is not just a definition-by-name — it is a genuine mathematical function, and everything about the semantics of propositional logic flows from these functions.

An interpretation (also called a valuation) assigns a truth value — T or F — to each atomic proposition. There are only two choices per atom, so for n atoms there are exactly 2n distinct interpretations. Given an interpretation, the truth value of any complex formula is computed mechanically by applying truth functions bottom-up through the formula's parse tree. For example, under the interpretation where A = T and B = F: (A ∧ B) applies the conjunction function to (T, F), returning F; (A → B) applies the material conditional function to (T, F), returning F; and ¬(A ∧ ¬B) requires evaluating ¬B = T, then A ∧ T = T, then ¬T = F. No intuition about meaning is needed — only the functions.

The fundamental lesson from your propositional semantics background is that formulas do not have truth values in themselves — they only have truth values relative to interpretations. The formula (A ∨ ¬A) is a tautology: it evaluates to T under every possible interpretation, because regardless of what A is, either A is T or ¬A is T. The formula (A ∧ ¬A) is a contradiction: it evaluates to F under every interpretation. Most formulas are contingent: true under some interpretations and false under others. A truth table exhausts all 2n interpretations, making this classification systematic.

The deeper point is what truth functions reveal about logical equivalence. Two formulas φ and ψ are logically equivalent (written φ ≡ ψ) exactly when they agree under every interpretation — they define the same truth function. This gives you a decision procedure for propositional logic: build truth tables for both formulas and compare column by column. The connectives →, ↔, and ⊕ (exclusive or) are all just specific truth functions, and any boolean function can be expressed using ∧, ∨, and ¬ alone (completeness of connectives). This connection between truth functions and logic is what makes propositional logic computationally tractable — and it sets the stage for understanding why predicate logic, which introduces quantifiers, is fundamentally harder.

Practice Questions 5 questions

Prerequisite Chain

Understanding Zero → The Number Zero → Counting to Five → Counting to 10 → Counting to 20 → Counting a Set of Objects Up to 20 → Cardinality: The Last Number Counted → Matching Numerals to Quantities → Subitizing Small Quantities → Addition Within 10 → Number Bonds to 10 → Addition Within 20 → Doubles and Near Doubles → Doubles Facts Within 10 → Near Doubles Facts Within 20 → Mental Math Strategies for Addition → Mental Math: Adding and Subtracting Tens → Addition Within 100 → Repeated Addition as Multiplication → Multiplication as Equal Groups → Multiplication: Arrays → Basic Multiplication Facts (0s, 1s, 2s, 5s, 10s) → Multiplication Facts Within 100 → Division as Equal Sharing → Division as Grouping (Measurement Division) → Division: Grouping (Repeated Subtraction) Model → Division: Fair Sharing Model → Division as Equal Sharing → Division as Grouping → Basic Division Facts → Division Facts Within 100 → Multiplication and Division Fact Families → Relationship Between Multiplication and Division → Division Facts as Inverse of Multiplication → Remainders and Quotients in Division → Division Word Problems → Multi-Step Word Problems → Solving Multi-Step Word Problems → Multiplication Word Problems → Division Word Problems → Introduction to Long Division → Factors and Multiples → Prime and Composite Numbers → Equivalent Fractions → Relating Fractions and Decimals → Decimal Place Value → Integers and the Number Line → Comparing and Ordering Integers → Absolute Value → Adding Integers → Subtracting Integers → Multiplying Integers → Introduction to Exponents → Order of Operations → Integer Order of Operations → Variable Expressions → The Distributive Property → Variables and Expressions Review → Introduction to Polynomials → Adding and Subtracting Polynomials → Multiplying Polynomials → Factorial → Permutations → Combinations → Counting Principles: Addition and Multiplication Rules → Introduction to Graph Theory → Propositional Logic Foundations → Logical Equivalences → Boolean Algebra → Introduction to Propositional Logic → Propositional Connectives → Propositional Semantics and Valuations → Truth Functions and Interpretation

Longest path: 73 steps · 323 total prerequisite topics

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