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Finite Model Theory Lecture 5 Turing Machines and Finite Models 1 Outline • Trakhtenbrot’s theorem (Chapter 9.1) • Fagin’s theorem (Chapter 9.2) 2 Trachtenbrot’s Theorem Definition. f is finitely satisfiable if there exists a finite model A s.t. A ² f Theorem [Trakhtenbrot] Suppose s has at least one relation symbol of arity ¸ 2. Then it is undecidable whether a sentence f is finitely satisfiable. 3 Consequence 1 Corollary. There is no recursive function f such that if f has a finite model then it has a finite model of size at most f(|f|). 4 Consequence 2 Definition. A sentence f is finitely valid, ²fin f, if for all finite models A, A ² f Question: is there a complete proof system `, i.e. such that ` f iff ²fin f ? Answer: NO ! [why ?] 5 Proof of Trakhtenbrot’s Theorem By reduction from the halting problem: given a Turing machine M, does it halt on the empty tape ? Given M, construct fM s.t. M halts iff fM has a finite model 6 Proof of Trakhtenbrot’s Theorem M halts: 9 C. (C is a halting computation of M) fM has a finite model: 9 A. A ² fM Hence a model A should stand for a computation of M 7 Proof of Trakhtenbrot’s Theorem Details: • M = (Q, D, d, q0, Qa) – states Q, initial state q0 2 Q, accepting states Qa µ Q – D = {0, 1} = tape alphabet – d = transitions • What is a computation C of M ? 8 Proof of Trakhtenbrot’s Theorem s = {<, T0(¢,¢), T1(¢, ¢), (Hq(¢, ¢))q 2 Q} The formula fM will say the following: • < is a linear order • T0(p, t) = the tape holds 0 at position p and time t • T1(p, t) = similar • Hq(p, t) = the machine is in state q at time t, and the head is over position p of the tape [write fM in class] A ² fM iff A represents a valid computation of M 9 Fagin’s Theorem • Recall Second Order Logic, SO: – May have formulas of the form 9 R.f or 8 R. f, where R is a relation symbol • Every SO formula can be written in prenex form like this: Q1 R1 … Qm Rm. f where each Qi is either 9 or 8, and f is in FO [WHY ???] 10 Fagin’s Theorem • Define 9 SO to be formulas of the form: 9 R1 … 9 Rm. f • Define 8 SO to be formulas of the form: 8 R1 … 8 Rm. f 11 Examples • Let s = {R}, i.e. a single binary relation. Finite models are graphs. • Express the following in SO – The graph is connected [what 2nd order quantifiers did we need ?] – The graph is 3-colorable – The graph has a Hamiltonean path 12 Examples 3-colorability: 9 A.9 B.9 C.(f Æ yA Æ yB Æ yC) f = 8 x.(A(x) Ç B(x) Ç C(x)) yA = 8 x.8 y.(R(x,y) ) : (A(x) Æ A(y))) yB = 8 x.8 y.(R(x,y) ) : (B(x) Æ B(y))) yC = 8 x.8 y.(R(x,y) ) : (C(x) Æ C(y))) 13 Examples Hamiltonean path: 9 <. (f Æ y) f = says that < is a total linear order y = says that if x<y are consecutive, then R(x,y) Little dirty secret of SO (actually 9 SO): we don’t need order, because we can express it ! 14 Fagin’s Theorem Theorem [Fagin] 9SO captures precisely NP More precisely: • For every f 2 9SO, the problem of checking whether A ² f is in NP • For any property of models, P, s.t. checking A 2 P is in NP, there exists a formula f 2 9SO s.t. A ² f iff A 2 P 15 Fagin’s Theorem Need encodings of finite structures: Let A = (A, R1A, …, RpA) where A = {a1, …, an} Fix an order a1 < a2 < … < an enc(A) = 0n¢ 1 ¢ enc(R1A) ¢ ¢ ¢ enc(RpA) where each enc(RiA) is a string of length nk in {0,1}* [what meaning ? See book pp. 88] 16 Proof • 9SO µ NP is obvious [why ?] • NP µ 9SO requires us to model a Turing Machine M running in NP with a formula fM: like in Trakhtenbrot’s theorem, with some additional complications 9 <. 9 T0. 9 T1 9 Hq1 … 9 Hqm. fM [what are the arities of T0, T1, (Hq)q 2 Q ? 17 Discussion • This is a characterization that does not mention computational resources ! • Later, other complexity classes were captured by logics, but for all lower classes Logic need help from order. Descriptive complexity 18 Fagin’s Theorem and P NP • We have NP = 9 SO, coNP = 8 SO • If we prove 9 SO 8 SO then P NP Definition. MSO = Monadic SO (restrict quantifiers to unary relations) Definition. Monadic NP = 9MSO; Monadic coNP = 8MSO [give examples of NP-complete problems in monadic NP] 19 Fagin’s Theorem and P NP Theorem Monadic NP Monadic coNP Proof. Step 1: Graph connectivity is in 8 MSO Step 2: Graph connectivity is not in 9 MSO 20