theory of languages and -...
TRANSCRIPT
Theory of Languages
and Automata
Chapter 0 - Introduction
Sharif University of Technology
ReferencesO Main Reference
M. Sipser, ”Introduction to the Theory of Computation,” 3nd Ed.,
Cengage Learning , 2013.
O Additional References
P. Linz, “An Introduction to Formal Languages and Automata,” 3rd
Ed., Jones and Barlett Publishers, Inc., 2001.
J.E. Hopcroft, R. Motwani and J.D. Ullman, “Introduction to
Automata Theory, Languages, and Computation,” 2nd Ed.,
Addison-Wesley, 2001.
P.J. Denning, J.B. Dennnis, and J.E. Qualitz, “Machines,
Languages, and Computation,” Prentice-Hall, Inc., 1978.
P.J. Cameron, “Sets, Logic and Categories,” Springer-Verlag,
London limited, 1998.
Prof. MovagharTheory of Languages and Automata 2
Grading Policy
O Assignments 20-30%
O First Quiz 10-15%
O Second Quiz 10-15%
O Final Exam 50%
Prof. MovagharTheory of Languages and Automata 3
Main Topics
O Complexity Theory
O Computability Theory
O Automata Theory
O Mathematical Notions
O Alphabet
O Strings
O Languages
Prof. MovagharTheory of Languages and Automata 5
Complexity Theory
O The scheme for classifying problems according to their computational difficulty
O Options:
Alter the problem to a more easily solvable one by understanding the root of difficulty
Approximate the perfect solution
Use a procedure that occasionally is slow but usually runs quickly
Consider alternatives, such as randomized computation
O Applied area:
Cryptography
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Computability Theory
O Determining whether a problem is solvable by
Computers
O Classification of problems as solvable ones and
unsolvable ones
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Automata Theory
O Definitions and properties of mathematical models
of computation
Finite automaton
Usage: Text Processing, Compilers, Hardware Design
Context-free grammar
Usage: Programming Languages, Artificial Intelligence
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Logic
O The science of the formal principles of
reasoning
Prof. MovagharTheory of Languages and Automata 9
History of Logic
O Logic was known as 'dialectic' or 'analytic' in Ancient Greece. The word 'logic' (from the Greek logos, meaning discourse or sentence) does not appear in the modern sense until the commentaries of Alexander of Aphrodisias, writing in the third century A.D.
O While many cultures have employed intricate systems of reasoning, and logical methods are evident in all human thought, an explicit analysis of the principles of reasoning was developed only in three traditions: those of China, India, and Greece.
Prof. MovagharTheory of Languages and Automata 10
History of Logic (cont.)
O Although exact dates are uncertain, particularly in the case of
India, it is possible that logic emerged in all three societies by
the 4th century BC.
O The formally sophisticated treatment of modern logic
descends from the Greek tradition, particularly Aristotelian
logic, which was further developed by Islamic Logicians and
then medieval European logicians.
O The work of Frege in the 19th century marked a radical
departure from the Aristotlian leading to the rapid
development of symbolic logic, later called mathematical
logic.
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Modern Logic
O Descartes proposed using algebra, especially techniques for solving for unknown quantities in equations, as a vehicle for scientific exploration.
O The idea of a calculus of reasoning was also developed by Leibniz. He was the first to formulate the notion of a broadly applicable system of mathematical logic.
O Frege in his 1879 work extended formal logic beyond propositional logic to include quantificationto represent the "all", "some" propositions of Aristotelian logic.
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Modern Logic (cont.)
O A logic is a language of formulas.
O A formula is a finite sequence of symbols with a
syntax and semantics.
O A logic can have a formal system.
O A formal system consists of a set of axioms and
rules of inference.
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Logic Types of Interest
O Propositional Logic
O Predicate Logic
Prof. MovagharTheory of Languages and Automata 14
Syntax of Propositional Logic
O Let {p0, p1, ..} be a countable set of
propositional variables,
O {, , ¬, →, ↔} be a finite set of
connectives,
O Also, there are left and right brackets,
O A propositional variable is a formula,
O If φ and ψ are formulas, then so are (¬φ), (φ ψ),
(φ ψ), (φ → ψ), and (φ ↔ ψ).
Prof. MovagharTheory of Languages and Automata 15
Semantics of Propositional Logic
O Any formula, which involves the propositional
variables p0,...,pn , can be used to define a function
of n variables, that is, a function from the set {T, F}n
to {T, F}. This function is often represented as the
truth table of the formula and is defined to be the
semantics of that formula.
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Examples
ψ φ (¬φ) (φ ψ) (φ ψ) (φ → ψ) (φ ↔ψ)
T T F T T T T
F T F F T F F
T F T F T T F
F F T F F T T
Prof. MovagharTheory of Languages and Automata 17
Other Definitions
O A formulae is a tautology if it is always true.
(P (¬P)) is a tautology.
O A formulae is a contradiction if it is never true.
(P (¬P)) is a contradiction.
O A formulae is a contingency if it is sometimes true.
(P → (¬P)) is a contingency.
Prof. MovagharTheory of Languages and Automata 18
Formal System
A formal system includes the following:
O An alphabet A, a set of symbols.
O A set of formulae, each of which is a string of
symbols from A.
O A set of axioms, each axiom being a formula.
O A set of rules of inference, each of which takes as
‘input’ a finite sequence of formulae and produces
as output a formula.
Prof. MovagharTheory of Languages and Automata 19
Proof
O A proof in a formal system is just a finite
sequence of formulae such that each formula
in the sequence either is an axiom or is
obtained from earlier formulae by applying a
rule of inference.
Prof. MovagharTheory of Languages and Automata 20
Theorem
O A theorem of the formal system is just the
last formula in a proof.
O Example:
For any formula φ, the formula (φ→φ) is a
theorem of the propositional logic.
Prof. MovagharTheory of Languages and Automata 21
A Formal System for Propositional
Logic
O There are three ‘schemes’ of axioms, namely:
(A1) (φ→(ψ → φ))
(A2) (φ→(ψ → θ)) → ((φ→ ψ) → (φ → θ))
(A3) (((¬φ) →(¬ψ)) → (ψ → φ))
O Each of these formulas is an axiom, for all choices
of formulae φ, ψ, θ.
O There is only one rule of inference, namely Modus
Ponens: From φ and (φ→ ψ), infer ψ.
Prof. MovagharTheory of Languages and Automata 22
Example of a Proof
O Using (A2), taking φ, ψ, θ to be φ, (φ→φ) and φrespectively
((φ→((φ→φ)→φ))→((φ→(φ→φ))→(φ →φ)))
O Using (A1), taking φ, ψ to be φ and (φ→φ) respectively
(φ→((φ→φ)→φ))
O Using Modus Ponens
((φ→(φ→φ))→(φ →φ))
O Using (A1), taking φ, ψ to be φ and φ respectively
(φ→(φ→φ))
O Using Modus Ponens
(φ→φ)
Prof. MovagharTheory of Languages and Automata 23
Soundness & Completeness
O A formal system is said to be sound if all
theorems in that system are tautology.
O A formal system is said to be complete if all
tautologies in that system are theorems.
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Predicate
O A proposition involving some variables,
functions and relations
O Example
P(x) = “x > 3”
Q(x,y,z) = “x2 + y2 = z2”
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Quantifier
O Universal: “for all” ∀
∀x P(x) ⇔ P(x1) ∧ P(x2) ∧ P(x3) ∧ …
O Existential: “there exists” ∃
∃x P(x) ⇔ P(x1) ∨ P(x2) ∨ P(x3) ∨ …
O Combinations:
∀x ∃y y > x
Prof. MovagharTheory of Languages and Automata 26
Quantifiers: Negation
O ¬ (∀x P(x)) ⇔ ∃x ¬ P(x)
O ¬ (∃x P(x)) ⇔ ∀x ¬ P(x)
O ¬ ∃x ∀y P(x,y) ⇔ ∀x ∃y ¬ P(x,y)
O ¬ ∀x ∃y P(x,y) ⇔ ∃x ∀y ¬ P(x,y)
Prof. MovagharTheory of Languages and Automata 27
Rules of Inference
1. Direct Proof
2. Indirect Proof
3. Proof by Contradiction
4. Proof by Cases
5. Induction
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Direct Proof
O If the two propositions (premises) p and p → q are
theorems, we may deduce that the proposition q is
also a theorem.
O This fundamental rule of inference is called modus
ponens by logicians.
p → q
p
∴ q
Prof. MovagharTheory of Languages and Automata 29
Indirect Proof
O Proves p → q by instead proving the contra-
positive, ~q → ~p
p → q
~q
∴ ~p
Prof. MovagharTheory of Languages and Automata 30
Proof by Contradiction
O The rule of inference used is that from
theorems p and ¬q → ¬p, we may deduce
theorem q.
p
~q → ~p
∴ q
Prof. MovagharTheory of Languages and Automata 31
Proof by Cases
O You want to prove p → q
O P can be decomposed to some cases:
p ↔ p1 ν p2 ν …ν pn
O Independently prove the n implications given
by
pi → q for 1 ≤ i ≤ n.
Prof. MovagharTheory of Languages and Automata 32
Proof by Induction
O To prove
1. Proof P(0),
2. Proof
( )xP x
[ ( ) ( 1)]x P x P x
Prof. MovagharTheory of Languages and Automata 33
Constructive Existence Proof
O Want to prove that
O Find an a and then prove that P(a) is true
)(xPx
Prof. MovagharTheory of Languages and Automata 34
Non-Constructive Existence Proof
O Want to prove that
O You cannot find an a that P(a) is true
O Then, you can use proof by contradiction:
)(xPx
FxPxxPx )(~)(~
Prof. MovagharTheory of Languages and Automata 35
Intuitive (Naïve) Set Theory
There are three basic concepts in set theory:
O Membership
O Extension
O Abstraction
Prof. MovagharTheory of Languages and Automata 36
Membership
O Membership is a relation that holds between a set
and an object
O x∈A to mean “the object x is a member of the set A”,
or “x belongs to A”. The negation of this assertion
is written x∉A as an abbreviation for the proposition
¬(x∈A)
O One way to specify a set is to list its elements. For
example, the set A = {a, b, c} consists of three
elements. For this set A, it is true that a∈A but d∉A
Prof. MovagharTheory of Languages and Automata 37
Extension
O The concept of extension is that two sets are
identical if and if only if they contain the
same elements. Thus we write A=B to mean
∀x [x∈A ⟺ x∈B]
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Abstraction
Each property defines a set, and each set defines a
property
O If p(x) is a property then we can define a set A
A = {x ∣ p(x)}
O If A is a set then we can define a predicate p(x)
p(x) = x∈A
Prof. MovagharTheory of Languages and Automata 39
Intuitive versus axiomatic set theory
O The theory of set built on the intuitive concept of
membership, extension, and abstraction is known as
intuitive (naïve) set theory.
O As an axiomatic theory of sets, it is not entirely
satisfactory, because the principle of abstraction
leads to contradictions when applied to certain
simple predicates.
Prof. MovagharTheory of Languages and Automata 40
Russell’s Paradox
Let p(X) be a predicate defined as
P(X) = (XX)
Define set R as
R={X|P(X)}
O Is P(R) true?
O Is P(R) false?
Prof. MovagharTheory of Languages and Automata 41
Gottlob Frege’s Comments
O The logician Gottlob Frege was the first to develop
mathematics on the foundation of set theory. He
learned of Russell Paradox while his work was in
press, and wrote, “A scientist can hardly meet with
anything more undesirable than to have the
foundation give way just as the work is finished. In
this position I was put by a letter from Mr. Bertrand
Russell as the work was nearly through the press.”
Prof. MovagharTheory of Languages and Automata 42
Power Set
O The set of all subsets of a given set A is
known as the power set of A, and is denoted
by P(A):
P(A) = {B | B A}
Prof. MovagharTheory of Languages and Automata 43
Set Operation-Union
O The union of two sets A and B is
A B = {x | (x A) (x B)}
and consists of those elements in at least one of A
and B.
O If A1, …, An constitute a family of sets, their union is
= (A1 … An)
= {x| x Ai for some i, 1≤ i ≤ n}
Prof. MovagharTheory of Languages and Automata 44
Set Operation-Intersection
O The intersection of two sets A and B is
A B = {x | (x A) ∧ (x B)}
and consists of those elements in at least one of Aand B.
O If A1, …, An constitute a family of sets, their intersection is
= (A1 … An)
= {x| x Ai for all i, 1≤ i ≤ n}
Prof. MovagharTheory of Languages and Automata 45
Set Operation-Complement
O The complement of a set A is a set Ac defined as:
Ac = {x | x ∉ A}
O The complement of a set B with respect to A, also
denoted as A-B, is defined as:
A-B = {x ∈ A | x ∉ B}
Prof. MovagharTheory of Languages and Automata 46
Ordered Pairs and n-tuples
O An ordered pair of elements is written
(x,y)
where x is known as the first element, and y is known
as the second element.
O An n-tuple is an ordered sequence of elements
(x1, x2, …, xn)
And is a generalization of an ordered pair.
Prof. MovagharTheory of Languages and Automata 47
Ordered Sets and Set Products
O By Cartesian product of two sets A and B, we mean
the set
A×B = {(x,y) | xA , yB}
O Similarly,
A1×A2×…An = {x1A1, x2A2, …, xnAn}
Prof. MovagharTheory of Languages and Automata 48
Relations
A relation ρ between sets A and B is a subset of A×B:
ρ A×B
O The domain of ρ is defined as
Dρ = {x A | for some y B, (x,y) ρ}
O The range of ρ is defined as
Rρ = {y B | for some x A, (x,y) ρ}
O If ρ A×A, then ρ is called a ”relation on A”.
Prof. MovagharTheory of Languages and Automata 49
Types of Relations on Sets
O A relation ρ is reflexive if
(x,x) ρ, for each x A
O A relation ρ is symmetric if, for all x,y A
(x,y) ρ implies (y,x) ρ
O A relation ρ is antisymmetric if, for all x,yA
(x,y) ρ and (y,x) ρ implies x=y
O A relation ρ is transitive if, for all x,y,z A
(x,y) ρ and (y,z) ρ implies (x,z) ρ
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Partial Order and Equivalence Relations
O A relation ρ on a set A is called a partial
ordering of A if ρ is reflexive, anti-symmetric,
and transitive.
O A relation ρ on a set A is called an equivalence
relation if ρ is reflexive, symmetric, and
transitive.
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Total Ordering
O A relation ρ on a set A is a total ordering if ρ
is a partial ordering and, for each pair of
elements (x,y) in A×A at least one of (x,y)ρ
or (y,x)ρ is true.
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Inverse Relation
O For any relation ρ A×B, the inverse of ρ is defined
by
ρ-1 = {(y,x) | (x,y) ρ}
O If Dρ and Rρ are the domain and range of ρ, then
Dρ-1 = Rρ and Rρ-1 = Dρ
Prof. MovagharTheory of Languages and Automata 53
Equivalence
O Let ρ A×A be an equivalence relation on A. The
equivalence class of an element x is defined as
[x] = {y A | (x,y) ρ}
O An equivalence relation on a set partitions the set.
Prof. MovagharTheory of Languages and Automata 54
Functions
A relation f A× B is a function if it has the property:
for all x,y,z, (x,y) f and (x,z) f implies y = z
O If f A× B is a function, we write
f: A → B
and say that f maps A into B. We use the common
notation
Y = f(x)
to mean (x,y) f.
Prof. MovagharTheory of Languages and Automata 55
Functions (cont.)
O As before, the domain of f is the set
Df = {x A | for some y B, (x,y) f}
and the range of f is the set
Rf = {y B | for some x A, (x,y) f}
O If Df A, we say the function is a partial function;
if Df = A, we say that f is a total function.
Prof. MovagharTheory of Languages and Automata 56
Functions (cont.)
O If x Df, we say that f is defined at x; otherwise f is
undefined at x.
O If Rf = B, we say that f maps Df onto B.
O If a function f has the property
for all x,y,z, f(x) = z and f(y) = z implies x = y
then f is a one-to-one function.
If f: A → B is a one-to-one function, f gives a one-to
one correspondence between elements of its domain
and range.
Prof. MovagharTheory of Languages and Automata 57
Functions (cont.)
O Let X be a set and suppose A X. Define function
CA: X → {0,1}
such that CA(x) = 1, if x A; CA(x) = 0, otherwise.
CA(x) is called the characteristic function of set A
with respect to set X.
O If f A× B is a function, then the inverse of f is the
set
f--1 = {(y,x) | (x,y) f}
f--1 is a function if and only if f is one-to-one.
Prof. MovagharTheory of Languages and Automata 58
Functions (cont.)
O Let f: A → B be a function, and suppose that X A.
Then the set
Y = f(X) = {y B | y = f(x) for some x X}
is known as the image of X under f.
O Similarly, the inverse image of a set Y included in
the range of f is
f -1(Y) = {x A | y = f(x) for some y Y}
Prof. MovagharTheory of Languages and Automata 59
Cardinality
O Two sets A and B are of equal cardinality, written as
|A| = |B|
if and only if there is a one-to-one function f: A → B
that maps A onto B.
O We write
|A| ≤ |B|
if B includes a subset C such that |A| = |C|.
O If |A| ≤ |B| and |A| ≠ |B|, then A has cardinality less than that of B, and we write
|A| < |B|
Prof. MovagharTheory of Languages and Automata 60
Cardinality (cont.)
O Let J = {1, 2, …} and Jn = {1, 2, …, n}.
O A sequence on a set X is a function f: J → X. A sequence
may be written as
f(1), f(2), f(3), …
However, we often use the simpler notation
x1, x2, x3, …., xi X
O A finite sequence of length n on X is a function
f: Jn → X, usually written as
x1, x2, x3, …., xn, xi X
O The sequence of length zero is the function f: → X.
Prof. MovagharTheory of Languages and Automata 61
Finite and Infinite Sets
O A set A is finite if |A| = |Jn| for some integer n ≥ 0, in which case we say that A has cardinality n.
O A set is infinite if it is not finite.
O A set X is denumerable if |X| = |J|.
O A set is countable if it is either finite or denumerable.
O A set is uncountable if it is not countable.
Prof. MovagharTheory of Languages and Automata 62
Some Properties
O Proposition: Every subset of J is countable.
Consequently, each subset of any denumerable set is
countable.
O Proposition: A function f: J → Y has a countable
range. Hence any function on a countable domain
has a countable range.
O Proposition: The set J × J is denumerable.
Therefore, A × B is countable for arbitrary
countable sets A and B.
Prof. MovagharTheory of Languages and Automata 63
Some Properties (cont.)
O Proposition: The set A B is countable whenever A
and B are countable sets.
O Proposition: Every infinite set X is at least
denumerable ; that is |X| ≥ |J|.
O Proposition: The set of all infinite sequence on {0, 1}
is uncountable.
Prof. MovagharTheory of Languages and Automata 64
Some Properties (cont.)
O Proposition: (Schröder-Bernestein Theorem)
For any set A and B, if |A| ≥ |B| and |B| ≥ |A|, then
|A| = |B|.
O Proposition: (Cantor’s Theorem)
For any set X,
|X| < |P(X)|.
Prof. MovagharTheory of Languages and Automata 65
1-1 correspondence Q↔N
O Proof (dove-tailing):
Prof. MovagharTheory of Languages and Automata 66
Countable Sets
O Any subset of a countable set
O The set of integers, algebraic/rational numbers
O The union of two/finite number of countable sets
O Cartesian product of a finite number of countable sets
O The set of all finite subsets of N
O Set of binary strings
Prof. MovagharTheory of Languages and Automata 67
Diagonal Argument
Prof. MovagharTheory of Languages and Automata 68
Uncountable Sets
O R, R2, P(N)
O The intervals [0,1), [0, 1], (0, 1)
O The set of all real numbers
O The set of all functions from N to {0, 1}
O The set of functions N → N
O Any set having an uncountable subset
Prof. MovagharTheory of Languages and Automata 69
Transfinite Cardinal Numbers
O Cardinality of a finite set is simply the number of
elements in the set.
O Cardinalities of infinite sets are not natural numbers,
but are special objects called transfinite cardinal
numbers.
O 0:|N|, is the first transfinite cardinal number.
O continuum hypothesis claims that |R|=1, the second
transfinite cardinal.
Prof. MovagharTheory of Languages and Automata 70
Alphabet
O A finite and nonempty set of symbols
(usually shown by ∑ or Г).
O Example:
σ = {𝑎, 𝑏, 𝑐, … , 𝑧}
Prof. MovagharTheory of Languages and Automata 71
Strings
O A finite list of symbols from an alphabet
O Example: house
O If ω is a string over ∑, the length of ω, written |ω|, is
the number of symbols that it contains.
O The empty string (ε or λ) is the string of length zero.
εω = ωε = ω
O String z is a substring of ω if z appears consecutively
within ω.
Prof. MovagharTheory of Languages and Automata 72
Operations on StringsO Reverse of a string:
w = a1a2…an ababaaabbb
wR = an…a2a1 bbbaaababa
O Concatenation:
w = a1a2…an abba
v = b1b2…bm bbbaaa
wv = a1a2…an b1b2…bm abbabbbaaa
|wv| = |w| + |v|
Prof. MovagharTheory of Languages and Automata 73
Operations on Alphabet
O * :
The set of all strings that can be produced from ∑.
O + :
The set of all strings, excluding λ, that can be produced from ∑.
Suppose that λ={λ}. Then:
Prof. MovagharTheory of Languages and Automata 74
Languages
O A set of strings
O Any language on the alphabet ∑ is a subset of ∑*.
O Examples:
Prof. MovagharTheory of Languages and Automata 75
Operations on Languages
Languages are a special kind of sets and operations on sets can be defined on them as well.
O Union
O Intersection
O Relative Complement
O Complement
λ, b, aa, ab, bb, aaa, …}
Prof. MovagharTheory of Languages and Automata 76
Operations on Languages (cont.)
O Reverse of a language
O Example:
Prof. MovagharTheory of Languages and Automata 77
Operations on Languages (cont.)
O Concatenation
O Example:
Prof. MovagharTheory of Languages and Automata 78
Operations on Languages (cont.)
O *: Kleene * The set of all strings that can be produced by concatenation
of strings of a language.
Example:
O +:
The set of all strings, excluding λ, that can be produced by concatenation of strings of a language.
Prof. MovagharTheory of Languages and Automata 79
Gödel Numbering
O Let ∑ be an alphabet containing n objects. Let h: ∑ → Jn
be an arbitrary one-to-one correspondence. Define
function f as:
f: ∑* → N
such that f(ε) =0; f(w.v) = n f(w) + h(v), for w ∑* and v ∑.
f is called a Gödel Numbering of ∑*.
O Proposition: ∑* is denumerable.
O Proposition: Any language on an alphabet is countable.
Prof. MovagharTheory of Languages and Automata 80