Lecture 9. Model theory. Consistency, independence, completeness, categoricity of axiom systems. Expanded with algebraic view.

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1 V. Borschev and B. Partee, October 17-19, 2006 p. 1 Lecture 9. Model theory. Consistency, independence, completeness, categoricity of axiom systems. Expanded with algebraic view. CONTENTS 0. Syntax and semantics; proof theory and model theory Syntactic provability and semantic entailment Semantic entailment and validity Soundness and completeness of a logic Consistency, completeness, independence, and other notions Some syntactic concepts Some semantic concepts Soundness and completeness again Independence Categoricity An algebraic view on provability and on the notions discussed above Closure systems Galois connection Morphisms for models; categoricity... 8 Appendix: An axiomatization of statement logic... 9 Appendix: Note on model-theoretic vs. proof-theoretic syntax... 9 Homework 9, due Oct Reading: Chapter 5, Chapter 8: , of PtMW, pp , Good supplementary reading: Fred Landman (1991) Structures for Semantics. Chapter 1, Sections 1.1 and 1.3., which we draw on heavily here. Another nice resource (thanks to Luis Alonso-Ovalle for the suggestion) is Gary Hardegree s online in-progress textbook Introduction to Metalogic : (Ch 5: the semantic characterization of logic, with notions of consistency, etc.; Ch 14: the semantics of classical first-order logic.) The notation is slightly different from ours and it may be hard to read those chapters in isolation, especially Ch 14, since the book is cumulative. Anyone who has a chance to take Hardegree s Mathematical Logic course would get a thorough grounding in all the notions we are discussing here and more. 0. Syntax and semantics; proof theory and model theory Starting out informally (see Chapter 5 of PtMW), we can say that the distinction between syntax and semantics in logic and formal systems is the distinction between talking about properties of expressions of the logic or formal system itself, such as its primitives, axioms, rules of inference or rewrite rules, and theorems, vs. talking about relations between the system and its models or interpretations. Examples: Syntactic activity: Constructing a proof from premises or axioms according to specified rules of inference or rewrite rules. (Proof theory is about this.) Semantic activity: Demonstrating that a certain set of axioms is consistent by showing that it has a model (see Section 2 below, or Ch. 8 in PtMW.) (Model theory is about such things.) Syntactic notions: Well-formedness, well-formedness rules, derivations, proofs, other notions definable in terms of the forms of expressions.

2 V. Borschev and B. Partee, October 17-19, 2006 p. 2 Semantic notions: truth, reference, valuation, satisfaction, assignment function, semantic entailment, and various other properties that relate expressions to models or interpretations. The program of studying only the syntax of a system without making any appeal, explicit or tacit, to its meaning constitutes the formalist research program, which is known as Hilbert s program in the foundations of mathematics, and, stretching the concept perhaps, as Chomsky s program of studying syntax autonomously in the theory of generative grammar. (PtMW p. 92) Irony: The term formal semantics refers to the model-theoretic semantics tradition that grew in part out of logician s model-theoretic approach to the study of the semantics of the formal languages of logic; that tradition is not formalist in Hilbert s sense, but is simply formal rather than informal. (The book of Montague s collected works is called Formal Philosophy; and cf. the use of formal in linguistics also to signal something like theoretical/explicit as opposed to practical/informal/descriptive.) We have already looked at the syntax and the semantics of statement logic and first-order predicate logic. Note that the syntax is in each case autonomous in the sense that it is fully described independently of the semantics, and the semantics is inherently relational, involving a compositional mapping from syntactic expressions to objects that belong to a model structure. 1. Syntactic provability and semantic entailment Proof theory: When we presented first order logic in earlier lectures, we specified only the syntax of well-formed formulas and their semantics. We did not give any proof theory, simply because we (unlike logicians) have not had proofs at the center of our interests. Let us add the bare basics of proof theory now. Specify for our first-order logic a set of axioms 1 and Rules of Inference, such as those described in Chapter 8.6 of PtMW or Chapter 1 of Landman. (We are not going to specify a set of axioms and rules of inference for first-order logic here, but see the Appendix for a complete axiomatization of statement logic, which is, of course, much simpler than that needed for predicate logic.) Then we can specify the notion of a proof of a formula ϕ from premises ϕ 1,..., ϕ n. A proof of a formula ϕ from premises ϕ 1,..., ϕ n is a finite sequence of formulas <ψ 1,..., ψ m > such that ψ m = ϕ, and each ψ i is either (a) an axiom, (b) a premise, or (c) inferred by means of one of the Rules of Inference from earlier formulas in the sequence. Call the resulting system of logic L0. An important aspect of the rules of inference is that they are strictly formal, i.e. syntactic : they apply when expressions are of the right form, with no need to know anything about their semantics. Corresponding notion of syntactic derivability or provability: (Landman p 8) Let be a set of formulas and φ a formula. We write φ, meaning φ is provable from, φ is derivable from, iff there is an L0-proof of φ from premises δ 1,..., δ n. The symbol is pronounced turnstile. (In Russian it is called shtopor, i.e. corkscrew.) 1 Here we consider axioms for first order predicate logic itself (PtMW 8.6), which we should distinguish from axioms for theories describing axiomatic classes of models. The former are tautologies which are true in every model. The latter are contingencies which are true in some models and false in other.

3 V. Borschev and B. Partee, October 17-19, 2006 p. 3 We write φ, φ is provable, φ is [syntactically] a tautology, for φ, i.e. φ is provable from the axioms and inference rules of the logic without further assumptions. φ is [syntactically] a contradiction if φ. It is common to use a special symbol ( bottom ) to stand for an arbitrary contradiction. Note that here we have introduced a syntactic notion of tautologies and contradictions. Our earlier definitions of tautologies in terms of truth-tables (for propositional logic) or truth in every model (for predicate logic) were semantic notions of tautology, and below we also consider corresponding semantic notions Semantic entailment and validity. Instead of writing [[φ ]] M,g = 1, it is customary when discussing model theory to write M φ[g], meaning φ is true in M relative to g. We write M φ (and say that φ is true in M) iff M φ[g] for all g. Other locutions: M satisfies φ, M is a model for φ. Note that if φ is a sentence (i.e., φ has no free variables), then for every model M, φ is true in M or φ is false in M. In general we are mostly interested in sentences, so we will often restrict ourselves to them. Let be a set of sentences and φ a sentence. Then we define φ, entails φ, iff for every model M it holds that: If M δ for every δ, then M φ. In other words, entails φ if φ is true in every model in which all the premises in are true. We write φ for φ. We say φ is valid, or logically valid, or a semantic tautology in that case. φ holds iff for every M, M φ. Validity means truth in all models Soundness and completeness of a logic. We have defined syntactic notions and semantic notions separately and independently; but we would of course be very dissatisfied with a logic which failed to provide a good correspondence between syntactic provability and semantic entailment. (We can make some such requirements a condition for any logic; see Hardegree s discussion of possible logics in his Chapter 7.) The notions of soundness and completeness relate to these correspondences. Soundness (of a logic): If L0 φ, then φ. I.e. anything you can prove is semantically valid. Our system of proofs doesn t give us anything bad. Completeness (of a logic): If φ, then L0 φ. Every argument that is semantically valid can be derived with the L0 rules. [Note: there are various different senses of complete ; this is one. On this sense, it is a LOGIC that is complete, sometimes called (strongly) semantically complete. We will see other senses in which a theory may be semantically or syntactically complete.]

4 V. Borschev and B. Partee, October 17-19, 2006 p. 4 Note: First-order predicate logic on any of its standard axiomatizations is sound and complete. Higher-order logics such as Montague s typed intensional logic are sound but often not complete. Soundness is an essential requirement; completeness isn t always possible. Completeness is one of the properties that makes first-order logic nice. 2. Consistency, completeness, independence, and other notions. (PtMW 8.5.2, Landman Chapter 1) Let L be a first order language. (I.e. we specify a particular set of individual constants and predicate constants (of various arities) for L; the rest of the specification of L follows from the definition of well-formed formulas of predicate logic.) A theory in L is a set of sentences of L. [This is Landman s usage; PtMW is slightly different; below, discussing the algebraic approach, we also will use this notion in a slightly different way] So a first order theory is a set of first order sentences Some syntactic concepts. Let be a theory. is inconsistent if. is consistent if /- (i.e. NOT ( ) ) I.e. a theory is inconsistent if you can derive a contradiction from it, consistent if you can t. It s often hard to prove that you can t derive a contradiction that requires a metalevel proof about possible proofs. We ll come to an easier semantic way of showing consistency in a minute. is deductively closed iff: if ϕ, then ϕ. Everything you can derive from is already in. is maximally consistent iff is consistent and there is no such that and and is consistent. c, the deductive closure of, is the set {ϕ : ϕ}. So c is the result of adding to every sentence that can be derived from. A theory is (formally) complete iff c, the deductive closure of, is maximally consistent. Equivalently, is formally complete if for every sentence ϕ in the language, either ϕ or ϕ. (This is the syntactic notion of completeness alluded to above.) Axioms and theories in the syntactic sense: is a set of axioms for Γ iff c = Γ c. Γ is finitely axiomatizable iff there is a finite set of axioms for Γ. Some facts (Landman p.11) FACT 1: If is consistent, then c is consistent. FACT 2: If is maximally consistent then is deductively closed. (Optional exercise: prove FACT 2.) FACT 3: (Deduction theorem) If {ϕ} ψ, then ( ψ ϕ). FACT 5: (Lindenbaum s Lemma) Any consistent theory can be extended to a maximally consistent theory.

5 V. Borschev and B. Partee, October 17-19, 2006 p Some semantic concepts. is satisfiable, equivalently has a model, iff there is a model M such that for all δ : M δ. is closed under logical consequence (under entailment) iff: if ϕ then ϕ. If ϕ is a sentence (i.e. has no free variables) and M ϕ, then we say that M is a model for ϕ, or ϕ holds in (or on) M. Similarly, we say that M is a model for theory, and we write M, if M is a model for every δ. Landman writes MOD(ϕ) for the class of all models for ϕ, and MOD( ) for the class of all models for. A set of axioms is semantically complete with respect to a model M, or weakly semantically complete, if every sentence which holds in M is derivable from. Three notions of completeness. We have now seen three notions of completeness: (i) a logic may be complete: everything which should be a theorem in the semantic sense, i.e. every sentence which is valid is indeed a theorem in the syntactic sense, i.e. is derivable, provable. (ii) Given a logic and a particular first-order language, a set of axioms is formally complete if the deductive closure of is maximally consistent: for every sentence, either it or its negation is provable from. (iii) A set of axioms is (weakly) semantically complete with respect to model M if every sentence which holds in M is derivable from. What do all these notions have in common? They all say that your logic or your axioms are sufficient to derive everything that meets a certain criterion; what varies is the criterion Soundness and completeness again. Another formulation of soundness and completeness for a logic, provably equivalent to the earlier one, is the following. Soundness (of a logic): If has a model, then is consistent. Completeness (of a logic): If is consistent, then has a model. Because first-order logic is sound and complete, we can freely choose whether to give a semantic or syntactic argument of consistency or inconsistency. Suppose you are asked to show whether some set of sentences is consistent or not. Usually if the answer is YES, the easiest way to show it is to show that has a model (by giving a model and showing, if it isn t obvious, that all of the sentences in hold in the model.) And if the answer is NO, usually the easiest way to show it is by deriving a contradiction, i.e. by showing that. See homework problems Independence. The notion of independence is less crucial than some of the other notions we have studied; it concerns the question of whether a given axiom within an axiom system is superfluous. There is nothing logically wrong with having some superfluous axioms; in fact they may make the system easier to work with (just as we typically work with two quantifiers and five connectives even though we know we could define some in terms of others.) But it is often an interesting issue, as

6 V. Borschev and B. Partee, October 17-19, 2006 p. 6 in the case of the discovery of non-euclidean geometries, which resulted from the quest to derive the fifth Euclidean postulate from the other four. The fifth postulate turned out to be independent of the others, and that was demonstrated by producing models (non-euclidean geometries) in which the first four postulates were true and the fifth one false. In general: if an axiom is not independent, you can prove it from the remaining axioms, and that is the standard way to prove non-independence. If an axiom is independent, the easiest way to show it is to produce a model that satisfies the remaining axioms but does not satisfy the one in question. See homework questions 2,3,4, Categoricity. An axiom system is categorical if all of its models are isomorphic. See more in Section 4 below, and see homework questions 3,6,8,10. Question 3 connects the notions of independence and categoricity. 3. An algebraic view on provability and on the notions discussed above [Here we use Universal Algebra by P.M. Cohn (1965), Harper & Row, New York, Evanston, and London] We will begin with extremely abstract (but simple) notions such as closure systems and Galois Connections. We will see how they clarify the notions we have just discussed Closure systems Let A be any set and (A) its power set, i.e. set of all its subsets. We wish to consider certain subsets of (A), or as we shall say, systems of subsets of A. A system R of subsets of A is said to be a closure system if R is closed under intersections, i.e. For any subsystem I R, we have I R In particular, taking I =, we see that A is always belong to R [if you don t see it don t despair, it is not always easy to think about intersection of empty set of sets 2 ; just take it that A always belongs to any closure system R of subsets of A by definition]. Note. (if you have heard of closure in topology): The algebraic notion of closure is similar to the topological one but weaker. Examples 1. The old one. The system of all subalgebras of a given algebra is a closure system. [Think why, it s is a good exercise] 2. Let S be a set of all sentences of some first order language. Then a) the set R D of all deductively closed theories is a closure system; b) the set R E of all theories closed under logical consequence (under entailment) is a closure system; c) R D = R E. [Think why 2 is true] 2 BHP doesn t see it, for instance. But VB does and will try to explain it if asked. Aha, wait, Dr. Math has a clear explanation: see The fact that the intersection of the empty family of sets is the universal set is one more example of a universal statement always coming out true on an empty domain, since the definition of intersection involves a universal quantifier.

7 V. Borschev and B. Partee, October 17-19, 2006 p. 7 Closure operator A closure operator on a set A is a mapping J of (A) in itself with the properties: J.1. If X Y, then J(X) J(Y) J.2. X J(X) J.3. JJ(X) = J(X) Theorem: Every closure system R on a set A defines a closure operator J on A by the rule J(X) = { Y R Y X}. Conversely, every closure operator J on A defines a closure system by R = { X A J(X) = X }, and the correspondence R J between closure systems and closure operators thus defined is bijective (one to one). [Try to prove that Theorem. Make use of the definitions of closure system and closure operator.] Examples Consider a set S of all sentences of some first order language and define operators J D and J E on S such that for every S 1. J D ( ) = c. 2. J E ( ) = ** where ** ={φ φ } It is easy to see that J D and J E are closure operators on S and J D = J E. In particular, if is a set of axioms for Γ then J D ( ) = J D (Γ) = c = Γ c Galois connection Let A and B be any sets and R A B a binary relation from A to B. For any subset X of A we define a subset X* of B by the equation X* = {y B <x,y> R for all x X } And similarly, for any subset Y of B we define a subset Y* of A by Y* = {x A <x,y> R for all y Y } Thus we have the mappings (1) f: (A) (B) and g: (B) (A) such that f(x) = X*, g(y) = Y* and it is easy to see that the properties (2) (4) hold (2) If X 1 X 2, then X 1 * X 2 *, If Y 1 Y 2, then Y 1 * Y 2 * (3) X X**, Y Y** (4) X*** = X*, Y*** = Y* Conditions (2) and (3) follow immediately from the definitions. If (2) is applied to (3) we get X* X***, while (3) applied to X* gives the reverse inequality. Thus any mappings (1) which satisfy (2) and (3) also satisfy (4). A pair of mappings (1) between (A) and (B) is called a Galois connection if it satisfies (2) and (3) (and hence (4).

8 V. Borschev and B. Partee, October 17-19, 2006 p. 8 To establish the link with closure systems we observe that in any Galois connection the mapping X X** is a closure operator in A and Y Y** is a closure operator in B (by (2)-(4)). Moreover, the mapping (1) gives a bijection between thes two closure systems. Examples 1. Our main example is a Galois connection based on a relation M ϕ (ϕ is valid in M) from class Mod(L) of all models for first order language L to the set S of all sentences of L. In this way we obtain a Galois connection between (Mod(L)) and (S). By this connection, (i) to any class MOD Mod(L), there corresponds the set MOD* of all sentences which are true in each M MOD, and (ii) to any set S there corresponds the class * of all those models in which all the sentences of are true. In a notation we used before, MOD* = {ϕ M ϕ for every M MOD } and * = MOD( ). So any model from the class * = MOD( ) is called a model for. Any sentence of MOD* is called a theorem in MOD. A class of models which is of the form * is said to be an axiomatic class and a set of its axioms. ** is the set of all theorems in * = MOD( ), a theory of * = MOD( ). So the semantic notion of axioms and theory given here corresponds to syntactic one given in 2.1 above. 2. Let Obj be a set of objects, Feat a set of their features, and R a relation from Obj to Feat to have a feature ( object O has a feature F ). The Galois connection based on this relation is similar to the previous one. It is used in Formal concepts theory, rather popular now. 4. Morphisms for models; categoricity Earlier we defined isomorphism, homomorphism, and automorphism for Ω-algebras: systems with a carrier set and operations of various arities on this carrier corresponding to symbols from the signature. Similar notions (different kinds of morphisms) are also considered for models. Describing Predicate Logic (the First Order Language) in the Lecture 6 we did not use the word signature but really used the notion. For every concrete language L we fix the set Const of constants and the set Pred of predicate symbols of different arities, Pred = Pred1 Pred 2 We can define the signature Ω of this language as a the union of its constants and predicate symbols, Ω = Const Pred. Then we can call all the models of this language of the kind M = <D,I> as models over signature Ω or Ω-models. Consider two Ω-models M = <D M,I M > and N = <D N,I N >. A mapping f: D M D N is called a homomorphism from M to N (and is denoted also as f: M N ) if (1) for every constant c Const, f(i M (c)) = I N (c) (2) for every n-ary predicate symbol P Pred and every n -tuple <d 1,, d n > D n M, if <d 1,, d n > I M (P) then <f(d 1 ),, f(d n ) > I N (P) A homomorphism f: M N is called an isomorphism between M and N if the inverse relation f 1 : D N D M is a function and it is a homomorphism.

9 V. Borschev and B. Partee, October 17-19, 2006 p. 9 An isomorphism f: M M is called an automorphism. An axiom system is called categorical if all of its models are isomorphic. (See homework questions 3,6,8.) Note. The notion of homomorphism for models is weaker than homomorphism for algebras. We have from the definition that for every n-tuple <d 1,, d n > I M (P) its image <f(d 1 ),, f(d n )> belongs to I N (P). But the opposite need not be true: if some n-tuple <d 1,, d n > doesn t belong to I M (P), its image <f(d 1 ),, f(d n )> can be in I N (P). So for every relation I M (P) in the model M, its image f(i M (P)) is a subset of corresponding relation I N (P) in the model N, i.e. we have f(i M (P)) I N (P), but we don t in general have the equality f(i M (P)) = I N (P). So in the case of models, in contrast to algebras, a bijective homomorphism f: M N (a homomorphism such that the mapping f: D M D N is a bijection (one-to-one and onto)) need not be an isomorphism between the models M and N because the inverse mapping f 1 : D N D M is not obligatorily a homomorphism. Appendix: An axiomatization of statement logic. This is from PtMW, Chapter 8.6, p This axiomatization of statement logic comes from Hilbert and Ackermann, who got it by deleting one non-independent axiom from the system of Whitehead and Russell s Principia Mathematica. This logic is provably complete, and its axioms are all independent. For more details and notational conventions, see PtMW, p.218. Axioms: A1: (p p) p A2. p (p q) A3. (p q) (q p) A4. (p q) ((r p) (r q)) Rules of Inference: R1: Rule of Substitution. For a statement variable in any statement Q we may substitute a statement P, provided that P is substituted for every occurrence of that statement variable in Q. [Note: this rule of inference is valid within the system of logic itself, where the premises are all tautologies and all rules of inference lead to further tautologies. It would not be a sound rule of inference within a formal system considering arbitrary contingent premises and deriving conclusions from them.] R2. Modus ponens. From P and P Q infer Q. [Unlike R2, this is valid everywhere.] From these four axioms with these two rules, all the tautologies of statement logic can be derived as theorems. Appendix: Note on model-theoretic vs. proof-theoretic syntax To see the link between proof theory in logic and derivations with respect to formal grammars, read Sections in PtMW (pp ). Model-theoretic syntax characterizes well-formed syntactic objects, e.g. trees for sentences of language L, not via derivations from a grammar but via a set of axioms ( constraints ) that each tree in L must satisfy; the set of well-formed trees for L then constitutes a model for that set of axioms. See the Postal extract that we will copy.

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