1 Finite Model Theory Lecture 14 Proof of the Pebble Games Theorem.

Slides:



Advertisements
Similar presentations
Completeness and Expressiveness
Advertisements

Some important properties Lectures of Prof. Doron Peled, Bar Ilan University.
Congestion and crowding Games Pasquale Ambrosio* Vincenzo Bonifaci + Carmine Ventre* *University of Salerno + University “La Sapienza” Roma.
1 In this lecture  Number Theory ● Rational numbers ● Divisibility  Proofs ● Direct proofs (cont.) ● Common mistakes in proofs ● Disproof by counterexample.
Lecture 7 Surreal Numbers. Lecture 7 Surreal Numbers.
6.896: Topics in Algorithmic Game Theory Lecture 11 Constantinos Daskalakis.
Congestion Games with Player- Specific Payoff Functions Igal Milchtaich, Department of Mathematics, The Hebrew University of Jerusalem, 1993 Presentation.
2.6 Prove Statements About Segments and Angles
Algebraic Structures: Group Theory II
If H is the subgroup in Z 12, then H2 = (a) 5(b) 14 (c) {3, 6, 9, 0}  {2}(d) {5, 8, 11, 2} (e) {5, 6, 9, 0}(f) {3, 2, 5}
The main idea of the article is to prove that there exist a tester of monotonicity with query and time complexity.
Assume f: A  B and g: B  C are functions. Which are defined? (1) f  g (2) g  f(3) both(4) neither.
Random Graphs and The Parity Quantifier Phokion G. Kolaitis Swastik Kopparty UC Santa Cruz MIT & & IBM Research-Almaden Institute for Advanced Study.
Transparency No Formal Language and Automata Theory Chapter 10 The Myhill-Nerode Theorem (lecture 15,16 and B)
How do we start this proof? (a) Assume A n is a subgroup of S n. (b)  (c) Assume o(S n ) = n! (d) Nonempty:
1 Finite Model Theory Lecture 10 Second Order Logic.
1 Finite Model Theory Lecture 13 FO k, L k 1, ,L  1, , and Pebble Games.
FSM Decomposition using Partitions on States 290N: The Unknown Component Problem Lecture 24.
How do we start this proof? (a) Let x  gHg -1. (b)  (c) Assume a, b  H (d) Show Nonempty:
Transparency No. 7-1 Formal Language and Automata Theory Chapter 7 Limitations of Finite Automata (lecture 11 and 12)
Umans Complexity Theory Lectures Lecture 2c: EXP Complete Problem: Padding and succinctness.
Lecture 4UofH - COSC Dr. Verma 1 COSC 3340: Introduction to Theory of Computation University of Houston Dr. Verma Lecture 4.
November 3, 2009Theory of Computation Lecture 14: A Universal Program VI 1 Recursively Enumerable Sets Definition: We write: W n = {x  N |  (x, n) 
Fact Families 1st Grade Wednesday, August 19, 2015Wednesday, August 19, 2015Wednesday, August 19, 2015Wednesday, August 19, 2015 Ms. Butler.
Math 3121 Abstract Algebra I Lecture 3 Sections 2-4: Binary Operations, Definition of Group.
Plan Lecture 3: 1. Fraisse Limits and Their Automaticity: a. Random Graphs. a. Random Graphs. b. Universal Partial Order. b. Universal Partial Order. 2.
MA4266 Topology Wayne Lawton Department of Mathematics S ,
Circuit Lower Bounds via Ehrenfeucht- Fraïssé Games Michal Koucký Joint work with: Clemens Lautemann, Sebastian Poloczek, Denis Thérien.
Great Theoretical Ideas in Computer Science for Some.
I.3 Introduction to the theory of convex conjugated function.
Chapter 5: Permutation Groups  Definitions and Notations  Cycle Notation  Properties of Permutations.
1 Finite Model Theory Lecture 3 Ehrenfeucht-Fraisse Games.
Math 344 Winter 07 Group Theory Part 2: Subgroups and Isomorphism
Relations Over Asymptotic Notations. Overview of Previous Lecture Although Estimation but Useful It is not always possible to determine behaviour of an.
CS Lecture 14 Powerful Tools     !. Build your toolbox of abstract structures and concepts. Know the capacities and limits of each tool.
1 Introduction to Quantum Information Processing CS 467 / CS 667 Phys 467 / Phys 767 C&O 481 / C&O 681 Richard Cleve DC 3524 Course.
SECTION 8 Groups of Permutations Definition A permutation of a set A is a function  ϕ : A  A that is both one to one and onto. If  and  are both permutations.
1 Finite Model Theory Lecture 16 L  1  Summary and 0/1 Laws.
Testing Low-Degree Polynomials over GF(2) Noga AlonSimon LitsynMichael Krivelevich Tali KaufmanDana Ron Danny Vainstein.
1 Finite Model Theory Lecture 5 Turing Machines and Finite Models.
Lecture 9: Query Complexity Tuesday, January 30, 2001.
MA4266 Topology Wayne Lawton Department of Mathematics S ,
1 Finite Model Theory Lecture 9 Logics and Complexity Classes (cont’d)
EXAMPLE FORMULA DEFINITION 1.
A useful reduction (SAT -> game)
Chapter 5 Limits and Continuity.
Finite Model Theory Lecture 8
Proving Statements about Segments
Great Theoretical Ideas In Computer Science
Chapter 3 The Real Numbers.
Umans Complexity Theory Lectures
Sets and Logic…. Chapters 5 and 6
2.5 Proving Statements about Segments
Alternating tree Automata and Parity games
Chapter 8: External Direct Product
Finite Model Theory Lecture 15
Finite Model Theory Lecture 2
Finite Model Theory Lecture 6
Lecture 10: Query Complexity
Theorem 6.30: A finite integral domain is a field.
Finite Model Theory Lecture 4
Section 2.5: Proving Statements about Segments
Last Night’s Homework: 2.2 Handout Tonight’s Homework: 2.3 Handout
Direct Proof and Counterexample IV
Category theory and structuralism
2.7 Proving Segment Relationships
2.7 Proving Statements about Segments
Richard Anderson Lecture 5 Graph Theory
LECTURE 2-9 PSPACE-Complete
COSC 3340: Introduction to Theory of Computation
Presentation transcript:

1 Finite Model Theory Lecture 14 Proof of the Pebble Games Theorem

2 More Motivation Recall connection to complexity classes: DTC + < = LOGSPACE TC + < = NLOGSPACE LFP + < = PTIME PFP + < = PSPACE

3 More Motivation Note: DTC = TC ) LOGSPACE = NLOGSPACE LFP = PFP ) PTIME = PSPACE What about the converse ? DTC ( TC (Paper 1) PTIME=PSPACE ) LFP = PFP (Paper 2)

4 EF v.s. Pebble Games Ehrenfeucht-Fraisse: k pebbles k rounds Main Theorem: Duplicator wins (A,B) iff A, B agree on all formulas in FO[k] Pebble games k pebbles n (or  ) rounds Main Theorem Duplicator wins for n (or  ) rounds iff A, B agree on all L  1,  [n] (or L k 1,  ) formulas

5 Back-and-forth For an ordinal , will define J  = { I ,  <  } to have the “back-and-forth” property I  = a set of partial isomorphisms from A to B Intuition: I  contains set of positions from which the duplicator can win if only  rounds remain Intuition: duplicator has a winning strategy for  rounds iff there exists a set J  with b&f property

6 Definition of B&F for J  For EF games: Forth: 8 f 2 I  8 a 2 A, 9 g 2 I  s.t. f µ g and a 2 dom(g) Back: symmetric Only need  < k Pebble games Forth: 8 f 2 I  |dom(f)| < k,  8 a 2 A, 9 g 2 I  s.t. f µ g and a 2 dom(g) Back: symmetric Downwards closed: if f µ g, g 2 I , then f 2 I  Antimonotone:  <  implies I  µ I  Nonempty: I   ;

7 B&F v.s. Games EF games: Duplicator wins (A,B) game iff there exists a family J k with the B&F property Pebble games: Duplicator wins (A,B) for  rounds iff there exists a family J  with the B&F property B&F stronger than games

8 The Proofs EF Lemma 1. Let A, B agree on all sentences in FO[k]. Then there exists a family J k with the B&F property Proof in class Pebble games Lemma 1. Let A, B agree on all sentences in L k 1,  of qr < . Then there exists a family J  with the B&F property Proof in class

9 The Proofs EF Lemma 2. Let A, B have a family J k with the B&F property. Then they agree on all formulas in FO[k] Proof in class Pebble games Lemma 2. Let A, B have a family J  with the B&F property. Then they agree on all sentences in L k 1,  of qr < . Proof in class