# Predicate Logic Review

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1 Predicate Logic Review UC Berkeley, Philosophy 142, Spring 2016 John MacFarlane 1 Grammar A term is an individual constant or a variable. An individual constant is a lowercase letter from the beginning of the alphabet, possibly with a numerical subscript. A variable is a lowercase w, x, y, or z, possibly with a numerical subscript. A predicate is a capital letter, possibly with a numerical subscript. Predicates can be classified as one-place, two-place, and in general n-place, depending on how many argument places they have. A logically perspicuous language would mark this, say, with a numerical superscript, but we will normally just leave it implicit. A formula is any of the following: term individual constant variable predicate formula An atomic formula an n-place predicate followed by n terms. (For example: atomic formula F xy, Ga.) 3. αφ or αφ, where α is a variable and φ is a formula. 4. φ, where φ is a formula. 5. (φ ψ), (φ ψ), (φ ψ), or (φ ψ), where φ and ψ are formulas. Nothing else is a formula. Note that in some texts (x) is used instead of x. Also, some texts put parentheses around x and x. We won t do that. 1.1 Scope The scope of a quantifier is the formula directly following the quantifier: scope In x(f x Gx), the scope of the quantifier is the formula (F x Gx). In xf x Gx, the scope of the quantifier is the formula F x. In x F x Ga, the scope of the quantifier is the formula F x. February 2,

2 2. Semantics A quantifier α or α will bind all occurrences of α within their scopes, except those that are already bound by other quantifiers. A variable that is not bound by a quantifier is called free. A formula containing free variables is called an open formula. A formula without free variables is called a closed formula or sentence. Exercises: bind free open formula closed formula sentence 1. Translate the following into logical notation. Provide a dictionary that associates individual constants and predicate letters with English names and predicates, and be sure to specify a domain. (a) A man who has not bathed repels every woman he meets. (b) Every philosopher trusts some lawyer who has sued one of his (the philosopher s) students. (c) Not all lawyers and philosophers are rich. 2. Translate the following into English (provide a dictionary you may make it up): (a) x(lx y(p y S xy)) (b) x((f x y(gy H xy)) z(c z Lx z)) 3. In each of the following sentences, circle the free variables and draw arrows from each of the bound variables to the quantifier that binds it. (a) x(f y Gxy) Gy x (b) x y(gxy xgy x) 2 Semantics In the Propositional Logic Review, we described a model as something that provides enough information to determine truth values for all of the formulas in a language. (In propositional logic, this is just an assignment of truth values to the propositional constants.) Now we must qualify that slightly: a model must determine truth values for all of the closed formulas (sentences) in a language. Open formulas do not have truth values. A model for our language of predicate logic consists in a nonempty set of objects the domain, and model domain an interpretation function, which assigns an interpretation to each individual constant and predicate letter. More specifically, it maps February 2,

3 2. Semantics each individual constant to an object in the domain each one-place predicate letter to a set of objects in the domain each two-place predicate letter to a set of ordered pairs of objects in the domain each n-place predicate letter to a set of ordered n-tuples of objects in the domain In specifying a model, we ll generally only write down the interpretations of individual constants and predicate letters that are relevant for our purposes, omitting the don t cares. Here are some examples of models (where F is a one-place predicate, G is a two-place predicate, and a is an individual constant): D = {1,2,3,8,Moses Hall} I ( F ) = {1,3} I ( G ) = { 1,2, 3,3 } (1) I ( a ) = Moses Hall D = the set of integers I ( F ) = {x : x > 0} I ( G ) = { x, y : x > y} (2) I ( a ) = 1 D = {x : x is a basketball player} I ( F ) = {x : x is Chinese} I ( G ) = { x, y : x is taller than y} (3) I ( a ) = Michael Jordan (You may not be familiar with the set-theoretic notation we use here. It s fairly simple. set-theoretic notation {1,2} denotes the set containing 1 and 2. {x : x is F } denotes the set containing every {} x such that x is F, that is, the set of F s. Angle brackets indicate ordered sequences. So, 1,2 is the sequence consisting of 1 and 2 in that order. 2,1 is a different sequence, because the order is different. By contrast, {1,2} and {2,1} are the same set, because sets are unordered.) We can also specify models informally using pictures (Fig. 1). We say that a sentence (that is, a closed formula) is true in a model just in case it is true in a model true when the quantifiers are interpreted as ranging over objects in the domain (and no others) and the individual constants and predicate letters are interpreted as having just the extensions assigned to them by the interpretation function. To state this condition more precisely, we need the notion of an assignment of values to the variables. An assignment is a function that maps each variable to an object in the assignment February 2,

4 2. Semantics Fido Rover Fluffy Tiger Figure 1: A model of x(d x yc xy) domain. We can now specify what it is for an arbitrary formula φ (open or closed) to be true in a model D, I on an assignment a. (Notation: a D,I φ, negated: a D,I φ.): a D,I φ, a D,I φ If φ is an atomic formula F α 1...α n, where F is an n-place predicate and α 1...α n are terms, a D,I φ iff α 1 a D,I,..., α n a I (F ), where D,I α a D,I = a(α) if α is a variable I (α) if α is an individual constant. If φ is, then a D,I φ. If φ is ψ, for some formula ψ, then a D,I φ iff a D,I ψ. If φ is (ψ χ ), for some formulas ψ and χ, then a D,I φ iff a D,I ψ and a D,I χ. If φ is (ψ χ ), for some formulas ψ and χ, then a D,I φ iff a D,I ψ or a D,I χ. If φ is (ψ χ ), for some formulas ψ and χ, then a D,I φ iff a D,I ψ or a D,I χ. If φ is (ψ χ ), for some formulas ψ and χ, then a D,I φ iff either a D,I ψ and a D,I χ or a D,I ψ and a D,I χ. If φ is αψ, for some variable α and formula ψ, then a φ iff for every assignment D,I a that agrees with a on the values of every variable except possibly α, a D,I ψ. If φ is αψ, for some variable α and formula ψ, then a φ iff for some assignment D,I a that agrees with a on the values of every variable except possibly α, a D,I ψ. Having defined the condition for any open or closed formula φ to be true in a model D, I on an assignment a, we can define truth in a model (not relativized to an assignment) for closed formulas as follows: A closed formula φ is true in a model D, I iff for every assignment a, a D,I φ. true in a model February 2,

5 3. Proofs (Note: we could have said some assignment instead of every assignment ; it doesn t matter, because if φ is a closed sentence, its truth won t vary from one assignment to the next.) The strategy for defining truth in a model that we have just outlined is due in its essentials to Alfred Tarski. It was one of his great achievements, because it showed logicians how to use semantic notions rigorously. Once we ve defined truth in a model, of course, we can define logical consequence, logical truth, logical equivalence, logical independence, and so on in the usual way. The definitions are just the same as in propositional logic, only we are now using more complicated models. Exercises: 1. For each of the three sample models on page 3, above, say which of the following sentences are true in that model: (a) x(f x Gxa) (b) x y(gxy Gy x) (c) x y Gy x 2. Complete the definitions, using the first line as a paradigm: (a) A sentence is logically true iff it is true in all models. (b) A sentence is logically false iff... (c) Two sentences are logically equivalent iff... (d) One sentence logically implies another iff... (e) A sentence (S) is a logical consequence of a set of sentences (Γ ) iff... (f) An argument is logically valid iff Use models to show the following: (a) x y F x y and y x F x y are not logically equivalent. (b) (F a xf x) F b is not a logical truth. (c) F a Gb does not logically imply x(f x Gx). 3 Proofs 3.1 Substitution instances A substitution instance of a quantified formula is the result of deleting the quantifier and its associated variable, then replacing every variable bound by the quantifier with the same substitution instance February 2,

6 3.2 Universal instantiation ( Elim) individual constant. Thus, for example, F aab is a substitution instance of xf x x b and also of yf yab, but not of xf xax. Note: An individual constant must be substituted for the bound variable. You may not substitute another kind of term, such as a variable or a definite description. (More liberal systems are possible, but the strict rule will simplify things when we get to definite descriptions.) 3.2 Universal instantiation ( Elim) You may write down any substitution instance of any universally quantified formula that is available at your current position in your proof, with the justification Elim (citing the line containing the quantified formula). Example: Elim 1 x y F xay hyp. 2 yf aay Elim 1 a/x (4) 3 yf bay Elim 1 b/x Notes: 1. It is a very good habit to indicate which constant is being substituted for which variable, as in the example. 2. There are no restrictions on which individual constant you use. Just be sure you replace every occurrence of the bound variable with the same constant. You can t use Elim to go from xf xax to F bax, because not every occurrence of the bound variable x was replaced by b. 3. A universally quantified formula is a formula whose main connective is. You can t use Elim to go from xf x xgx to F a Ga, because the former is not a universally quantified formula (the main connective is ). 3.3 Existential generalization ( Intro) If a substitution instance of an existentially quantified formula is available at your current position in the proof, you may write down the existentially quantified formula of which it is an instance, with the justification Intro (citing the line containing the instance). Example: Intro 1 y F aya hyp. 2 x yf xya Intro 1 a/x (5) 3 x yf xy x Intro 1 a/x February 2,

7 3.4 Universal generalization ( Intro) Notes: 1. An existentially quantified formula is a formula whose main connective is. xf x Ga is not an existentially quantified formula, and it can t be obtained by Intro from F b Ga. 2. Whereas in Elim you move from a quantified formula to an instance, in Intro you move from an instance to a quantified formula. 3. Note that line 1 above is an instance of both 2 and Universal generalization ( Intro) You can derive a universally quantified formula αφ from a subproof whose last step is a substitution instance, with an individual constant in place of α, and whose first step is a flagging step containing that individual constant in a box. The justification is Intro (citing the lines of the subproof). A flagging step is like a hypothesis, but instead of a formula, it consists of an individual constant in a box: 1 a Intro flagging step 2 There is one important restriction: the flagged constant may not occur outside of the subproof where it is introduced. So pick a constant that does not occur in the premises or conclusion or in any previous flagging step. The flagging step is a formal representation of Take an arbitrary individual call it Joe. We then argue that Joe has such and such a property, and since Joe was arbitrary, the same could be shown about any object. The flagging restrictions are there to make sure the individual is really arbitrary, not one that you have already said something about elsewhere in the proof. February 2,

8 3.5 Existential instantiation ( Elim) Example: 1 x(gx H x) 2 x(h x F x) 3 a 4 Ga H a Elim 1 a/x 5 H a F a Elim 2 a/x 6 Ga hyp (6) 7 H a Elim 4, 6 8 F a Elim 5, 7 9 Ga F a Intro x(gx F x) Intro 3 9 a/x 3.5 Existential instantiation ( Elim) If an existentially quantified formula is available at your current position in the proof, you may start a new subproof with an instance as a hypothesis and the instantial constant flagged in a box. You can close the subproof at any point where you have a formula not containing the flagged constant, and reiterate the final formula of the subproof outside of the subproof with justification Elim, citing the line containing the existentially quantified formula and the whole subproof. As before, the flagged constant may not occur outside of the subproof where it is introduced. This is easier to see with an example: Elim 1 x(gx H a) 2 Gb H a b b/x 3 Gb Elim 2 (7) 4 xgx Intro 3 5 xgx Elim 1, 2 4 Notes: 1. We could not have closed off the subproof after line 3, since the flagged constant cannot occur in the last line of the main proof. 2. We could not have used a as our flagged term in line 2, since it occurs in line 1. February 2,

9 3.6 Quantifier equivalences (QE) The Intro and Elim rules for and and the propositional connectives give us all we need for a complete proof system. But to make quantificational proofs less tedious, we will also allow the use of two more rules. 3.6 Quantifier equivalences (QE) You may use the following substitution rules at any point in a proof, citing QE and the line number as justification. Since they are substitution rules, they can operate on subformulas, not just on the main formula. They are also reversible. (See the examples to follow.) QE Quantifier equivalences xφ x φ (8) xφ x φ (9) Examples: 1 x(gx H a) 2 x (Gx H a) QE 1 (10) 1 H a x Gx 2 H a xgx QE 1 (11) Note that QE is applied to a subformula in example (11). The main connective in (1) is, not a quantifier. That s okay, because the QE rules are substitution rules, not rules of inference. 3.7 Tautological Equivalence (Taut Equiv) What if you wanted to derive x(gx H x) from x(gx H x)? Given the rules we have so far, you d have to take a circuitous path: Taut Equiv February 2,

10 3.7 Tautological Equivalence (Taut Equiv) 1 x(gx H x) 2 x (Gx H x) QE 1 3 b 4 (Gb H b) Elim, 2, b/x 5 Gb hyp 6 H b hyp (12) 7 Gb H b Intro, 5, 6 8 Intro, 4, 7 9 H b Intro, Gb H b Intro, x(g x H x) Intro, 3 10, b/x To simplify this kind of proof, we introduce a new substitution rule, Taut Equiv, that allows you to substitute truth-functionally equivalent formulas for each other, even when they occur embedded inside quantifiers or other operators. Then we can do: 1 x(gx H x) 2 x (Gx H x) QE 1 (13) 3 x(g x H x) Taut Equiv 2 We ll allow Taut Equiv only in proofs involving quantifiers. Note that Taut Equiv, like the QE rules and unlike the Intro and Elim rules, can operate on subformulas and is reversible. Exercises: 1. Use Fitch-style natural deductions to prove the following theorems: (a) x(f x Gx) ( xf x xgx) (b) x y zf xy z y z xf xy z 2. Use Fitch-style natural deductions to prove x(p x yly x) from hypotheses x(p x yf y x) and x y(f y x Ly x). February 2,

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