Lecture5Álvaro Cárdenas Here are the key steps in a direct proof of this theorem:
1) Assume r and s are rational numbers
2) By definition, there exist integers p,q and t,u such that r = p/q and s = t/u
3) Then r + s = (pq + tu)/qu
4) pq + tu and qu are integers
5) Therefore, by the definition, r + s is rational
So we have directly proven that if r and s are rational, then their sum is rational.
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Valid & invalid argumentsAbdur RehmanThe document discusses valid and invalid arguments in propositional logic. It defines arguments and their forms, and validity. It explains how to test an argument form for validity using a truth table. It then discusses several rules of inference for propositional logic including modus ponens, modus tollens, generalization, simplification, disjunctive syllogism, hypothetical syllogism, and provides examples of applying these rules. Finally, it discusses arguments with quantified statements and the rules of universal instantiation, universal modus ponens, and universal modus tollens.
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Intelligent agents should have the capacity for perceiving, representing knowledge, reasoning about what they know, and acting. Knowledge representation involves representing an understanding of the world, while reasoning involves inferring implications of what is known. Logic provides a way to represent and reason about knowledge through specifying a logical language with syntax, semantics, and inference rules.
rules of inference in discrete structuresZenLooperThe document discusses rules of inference in propositional logic. It defines rules of inference as templates for valid arguments that can be used to construct more complex arguments. Several common rules are described, including modus ponens, modus tollens, hypothetical syllogism, disjunctive syllogism, and resolution. Examples are provided to demonstrate how each rule works and how multiple rules can be combined to determine the validity of arguments with multiple premises.
rulesOfInference.pptssuserf1f9e8This document discusses rules of inference used in propositional logic and quantified statements. It defines rules like modus ponens, modus tollens, and universal instantiation that allow valid logical arguments to be constructed by moving from premises to a conclusion. An example argument is broken down step-by-step to demonstrate applying rules of inference like simplification, modus tollens, and modus ponens to derive a conclusion from a set of premises. Finally, inference rules for quantified statements including universal and existential generalization and instantiation are introduced.
Logic.pptsyedadamiyaThis document provides an overview of propositional logic and introduces first-order logic. It defines key concepts in propositional logic like logical connectives, truth tables, validity, and soundness. Examples are given of representing propositions and inferences. The limitations of propositional logic are discussed. First-order logic is then introduced as adding objects, properties, relations, functions, variables and quantifiers to increase expressiveness over propositional logic. Terms, atoms, and well-formed formulas are defined for first-order logic.
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- Different types of statements and their grammar.
- Propositional logic including symbols, connectives, truth tables, and semantics.
- Quantifiers, universal and existential quantification, and properties of quantifiers.
- Normal forms such as disjunctive normal form and conjunctive normal form.
- Inference rules and the principle of mathematical induction, illustrated with examples.
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Ch03 basic logical_conceptsHariz MustafaThe document discusses the key differences between deductive and inductive arguments. It notes that when evaluating an argument, one should consider whether the premises are true and whether the premises provide good reasons to accept the conclusion. For chapter 3, it will only focus on the latter. It provides examples of deductive and inductive arguments. It also outlines different ways to determine whether an argument is deductive or inductive, such as looking for indicator words, applying tests of strict necessity and charity, and identifying if the argument follows a commonly used pattern of deductive or inductive reasoning.
Jarrar.lecture notes.aai.2011s.ch7.p logicPalGovThe document discusses logic agents and logical reasoning. It provides background on logic, including syntax, semantics, models, and inference rules. It then discusses how logic can be used to represent knowledge in knowledge-based agents and systems. The agents use a knowledge base and inference engine, where the inference engine derives new knowledge by applying inference rules to the knowledge base.
Per3 pembuktianEvert Sandye TaasiringanThe document discusses mathematical reasoning and proofs. It provides definitions for key terminology used in proofs such as axioms, theorems, lemmas, and conjectures. It also explains rules of inference like modus ponens and rules for quantified statements. Examples are given to illustrate valid and invalid arguments as well as direct and indirect proofs of theorems.
Top school in delhi ncrEdhole.comThis document provides an overview of propositional logic and first-order logic. It begins with a review of propositional logic, including logical connectives, truth tables, and inference rules. It then discusses some limitations of propositional logic, such as its inability to represent properties, relations or generalizations. The document introduces first-order logic as a more expressive language that adds variables, quantifiers, relations and functions. It defines terms, atomic sentences, and well-formed formulas. Key concepts in first-order logic like universal and existential quantification are explained along with inference rules like universal instantiation.
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4. Section Summary
Valid Arguments
Inference Rules for Propositional Logic
Using Rules of Inference to Build Arguments
Rules of Inference for Quantified Statements
Building Arguments for Quantified Statements
5. Revisiting the Socrates Example
We have the two premises:
“All men are mortal.”
“Socrates is a man.”
And the conclusion:
“Socrates is mortal.”
How do we get the conclusion from the premises?
6. The Argument
We can express the premises (above the line) and the
conclusion (below the line) in predicate logic as an
argument:
We will see shortly that this is a valid argument.
7. Valid Arguments
We will show how to construct valid arguments in
two stages; first for propositional logic and then for
predicate logic. The rules of inference are the
essential building block in the construction of valid
arguments.
1. Propositional Logic
Inference Rules
2. Predicate Logic
Inference rules for propositional logic plus additional inference
rules to handle variables and quantifiers.
8. Arguments in Propositional Logic
A argument in propositional logic is a sequence of propositions.
All but the final proposition are called premises. The last
statement is the conclusion.
The argument is valid if the premises imply the conclusion. An
argument form is an argument that is valid no matter what
propositions are substituted into its propositional variables.
If the premises are p1 ,p2, …,pn and the conclusion is q then
(p1 ∧ p2 ∧ … ∧ pn ) → q is a tautology.
Inference rules are all argument simple argument forms that will
be used to construct more complex argument forms.
9. Rules of Inference for Propositional
Logic: Modus Ponens
Example:
Let p be “It is snowing.”
Let q be “I will study discrete math.”
“If it is snowing, then I will study discrete math.”
“It is snowing.”
“Therefore , I will study discrete math.”
Corresponding Tautology:
(p ∧ (p →q)) → q
10. Modus Tollens
Example:
Let p be “it is snowing.”
Let q be “I will study discrete math.”
“If it is snowing, then I will study discrete math.”
“I will not study discrete math.”
“Therefore , it is not snowing.”
Corresponding Tautology:
(¬q∧(p →q))→¬p
11. Hypothetical Syllogism
Example:
Let p be “it snows.”
Let q be “I will study discrete math.”
Let r be “I will get an A.”
“If it snows, then I will study discrete math.”
“If I study discrete math, I will get an A.”
“Therefore , If it snows, I will get an A.”
Corresponding Tautology:
((p →q) ∧ (q→r))→(p→ r)
12. Disjunctive Syllogism
Example:
Let p be “I will study discrete math.”
Let q be “I will study English literature.”
“I will study discrete math or I will study English literature.”
“I will not study discrete math.”
“Therefore , I will study English literature.”
Corresponding Tautology:
(¬p∧(p ∨q))→q
13. Addition
Example:
Let p be “I will study discrete math.”
Let q be “I will visit Las Vegas.”
“I will study discrete math.”
“Therefore, I will study discrete math or I will visit
Las Vegas.”
Corresponding Tautology:
p →(p ∨q)
14. Simplification
Example:
Let p be “I will study discrete math.”
Let q be “I will study English literature.”
“I will study discrete math and English literature”
“Therefore, I will study discrete math.”
Corresponding Tautology:
(p∧q) →p
15. Conjunction
Example:
Let p be “I will study discrete math.”
Let q be “I will study English literature.”
“I will study discrete math.”
“I will study English literature.”
“Therefore, I will study discrete math and I will study
English literature.”
Corresponding Tautology:
((p) ∧ (q)) →(p ∧ q)
16. Resolution
Example:
Let p be “I will study discrete math.”
Let r be “I will study English literature.”
Let q be “I will study databases.”
“I will not study discrete math or I will study English literature.”
“I will study discrete math or I will study databases.”
“Therefore, I will study databases or I will study English
literature.”
Corresponding Tautology:
((¬p ∨ r ) ∧ (p ∨ q)) →(q ∨ r)
Resolution plays an important role
in AI and is used in Prolog.
17. Using the Rules of Inference to
Build Valid Arguments
A valid argument is a sequence of statements. Each statement is
either a premise or follows from previous statements by rules of
inference. The last statement is called conclusion.
A valid argument takes the following form:
S1
S2
.
.
.
Sn
C
19. Valid Arguments
Example 2:
With these hypotheses:
“It is not sunny this afternoon and it is colder than yesterday.”
“We will go swimming only if it is sunny.”
“If we do not go swimming, then we will take a canoe trip.”
“If we take a canoe trip, then we will be home by sunset.”
Using the inference rules, construct a valid argument for the conclusion:
“We will be home by sunset.”
Solution:
1. Choose propositional variables:
p : “It is sunny this afternoon.” r : “We will go swimming.” t : “We will be home by sunset.”
q : “It is colder than yesterday.” s : “We will take a canoe trip.”
2. Translation into propositional logic:
Continued on next slide
21. Handling Quantified Statements
Valid arguments for quantified statements are a
sequence of statements. Each statement is either a
premise or follows from previous statements by rules
of inference which include:
Rules of Inference for Propositional Logic
Rules of Inference for Quantified Statements
The rules of inference for quantified statements are
introduced in the next several slides.
26. Using Rules of Inference
Example 1: Using the rules of inference, construct a valid
argument to show that
“John Smith has two legs”
is a consequence of the premises:
“Every man has two legs.” “John Smith is a man.”
Solution: Let M(x) denote “x is a man” and L(x) “ x has two legs”
and let John Smith be a member of the domain.
Valid Argument:
27. Using Rules of Inference
Example 2: Use the rules of inference to construct a valid argument
showing that the conclusion
“Someone who passed the first exam has not read the book.”
follows from the premises
“A student in this class has not read the book.”
“Everyone in this class passed the first exam.”
Solution: Let C(x) denote “x is in this class,” B(x) denote “ x has read
the book,” and P(x) denote “x passed the first exam.”
First we translate the
premises and conclusion
into symbolic form.
Continued on next slide
31. Universal Modus Ponens
Universal Modus Ponens combines universal
instantiation and modus ponens into one rule.
This rule could be used in the Socrates example.
33. Section Summary
Mathematical Proofs
Forms of Theorems
Direct Proofs
Indirect Proofs
Proof of the Contrapositive
Proof by Contradiction
34. Proofs of Mathematical Statements
A proof is a valid argument that establishes the truth of a
statement.
In math, CS, and other disciplines, informal proofs which are
generally shorter, are generally used.
More than one rule of inference are often used in a step.
Steps may be skipped.
The rules of inference used are not explicitly stated.
Easier for to understand and to explain to people.
But it is also easier to introduce errors.
Proofs have many practical applications:
verification that computer programs are correct
establishing that operating systems are secure
enabling programs to make inferences in artificial intelligence
showing that system specifications are consistent
35. Definitions
A theorem is a statement that can be shown to be true using:
definitions
other theorems
axioms (statements which are given as true)
rules of inference
A lemma is a ‘helping theorem’ or a result which is needed to
prove a theorem.
A corollary is a result which follows directly from a theorem.
Less important theorems are sometimes called propositions.
A conjecture is a statement that is being proposed to be true.
Once a proof of a conjecture is found, it becomes a theorem. It
may turn out to be false.
36. Forms of Theorems
Many theorems assert that a property holds for all elements
in a domain, such as the integers, the real numbers, or
some of the discrete structures that we will study in this
class.
Often the universal quantifier (needed for a precise
statement of a theorem) is omitted by standard
mathematical convention.
For example, the statement:
“If x > y, where x and y are positive real numbers, then x2 > y2 ”
really means
“For all positive real numbers x and y, if x > y, then x2 > y2 .”
37. Proving Theorems
Many theorems have the form:
To prove them, we show that where c is an arbitrary
element of the domain,
By universal generalization the truth of the original
formula follows.
So, we must prove something of the form:
38. Proving Conditional Statements: p → q
Trivial Proof: If we know q is true, then
p → q is true as well.
“If it is raining then 1=1.”
Vacuous Proof: If we know p is false then
p → q is true as well.
“If I am both rich and poor then 2 + 2 = 5.”
[ Even though these examples seem silly, both trivial and vacuous
proofs are often used in mathematical induction, as we will see
in Chapter 5) ]
39. Even and Odd Integers
Definition: The integer n is even if there exists an
integer k such that n = 2k, and n is odd if there exists
an integer k, such that n = 2k + 1. Note that every
integer is either even or odd and no integer is both
even and odd.
We will need this basic fact about the integers in some
of the example proofs to follow. We will learn more
about the integers in Chapter 4.
40. Proving Conditional Statements: p → q
Direct Proof: Assume that p is true. Use rules of inference,
axioms, and logical equivalences to show that q must also
be true.
Example: Give a direct proof of the theorem “If n is an odd
integer, then n2 is odd.”
Solution: Assume that n is odd. Then n = 2k + 1 for an
integer k. Squaring both sides of the equation, we get:
n2 = (2k + 1)2 = 4k2 + 4k +1 = 2(2k2 + 2k) + 1= 2r + 1,
where r = 2k2 + 2k , an integer.
We have proved that if n is an odd integer, then n2 is an
odd integer.
( marks the end of the proof. Sometimes QED is
used instead. )
41. Proving Conditional Statements: p → q
Definition: The real number r is rational if there exist
integers p and q where q≠0 such that r = p/q
Example: Prove that the sum of two rational numbers
is rational.
Solution: Assume r and s are two rational numbers.
Then there must be integers p, q and also t, u such
that
Thus the sum is rational.
where v = pu + qt
w = qu ≠ 0
42. Proving Conditional Statements: p → q
Proof by Contraposition: Assume ¬q and show ¬p is true also. This is
sometimes called an indirect proof method. If we give a direct proof of
¬q → ¬p then we have a proof of p → q.
Why does this work?
Example: Prove that if n is an integer and 3n + 2 is odd, then n is
odd.
Solution: Assume n is even. So, n = 2k for some integer k. Thus
3n + 2 = 3(2k) + 2 =6k +2 = 2(3k + 1) = 2j for j = 3k +1
Therefore 3n + 2 is even. Since we have shown ¬q → ¬p , p → q
must hold as well. If n is an integer and 3n + 2 is odd (not even) ,
then n is odd (not even).
43. Proving Conditional Statements: p → q
Example: Prove that for an integer n, if n2 is odd, then n is
odd.
Solution: Use proof by contraposition. Assume n is even
(i.e., not odd). Therefore, there exists an integer k such
that n = 2k. Hence,
n2 = 4k2 = 2 (2k2)
and n2 is even(i.e., not odd).
We have shown that if n is an even integer, then n2 is even.
Therefore by contraposition, for an integer n, if n2 is odd,
then n is odd.
44. Proving Conditional Statements: p → q
Proof by Contradiction: (AKA reductio ad absurdum).
To prove p, assume ¬p and derive a contradiction such as
p ∧ ¬p. (an indirect form of proof). Since we have shown
that ¬p →F is true , it follows that the contrapositive T→p
also holds.
Example: Prove that if you pick 22 days from the calendar,
at least 4 must fall on the same day of the week.
Solution: Assume that no more than 3 of the 22 days fall
on the same day of the week. Because there are 7 days of
the week, we could only have picked 21 days. This
contradicts the assumption that we have picked 22 days.
45. Proof by Contradiction
A preview of Chapter 4.
Example: Use a proof by contradiction to give a proof that √2 is
irrational.
Solution: Suppose √2 is rational. Then there exists integers a and b
with √2 = a/b, where b≠ 0 and a and b have no common factors (see
Chapter 4). Then
Therefore a2 must be even. If a2 is even then a must be even (an
exercise). Since a is even, a = 2c for some integer c. Thus,
Therefore b2 is even. Again then b must be even as well.
But then 2 must divide both a and b. This contradicts our assumption
that a and b have no common factors. We have proved by contradiction
that our initial assumption must be false and therefore √2 is
irrational .
46. Proof by Contradiction
A preview of Chapter 4.
Example: Prove that there is no largest prime number.
Solution: Assume that there is a largest prime number. Call
it pn. Hence, we can list all the primes 2,3,.., pn. Form
None of the prime numbers on the list divides r. Therefore,
by a theorem in Chapter 4, either r is prime or there is a
smaller prime that divides r. This contradicts the
assumption that there is a largest prime. Therefore, there is
no largest prime.
47. Theorems that are Biconditional
Statements
To prove a theorem that is a biconditional statement,
that is, a statement of the form p ↔ q, we show that
p → q and q →p are both true.
Example: Prove the theorem: “If n is an integer, then n is
odd if and only if n2 is odd.”
Solution: We have already shown (previous slides) that
both p →q and q →p. Therefore we can conclude p ↔ q.
Sometimes iff is used as an abbreviation for “if an only if,” as in
“If n is an integer, then n is odd iif n2 is odd.”
48. What is wrong with this?
“Proof” that 1 = 2
Solution: Step 5. a - b = 0 by the premise and
division by 0 is undefined.
49. Looking Ahead
If direct methods of proof do not work:
We may need a clever use of a proof by contraposition.
Or a proof by contradiction.
In the next section, we will see strategies that can be
used when straightforward approaches do not work.
In Chapter 5, we will see mathematical induction and
related techniques.
In Chapter 6, we will see combinatorial proofs
51. Section Summary
Proof by Cases
Existence Proofs
Constructive
Nonconstructive
Disproof by Counterexample
Nonexistence Proofs
Uniqueness Proofs
Proof Strategies
Proving Universally Quantified Assertions
Open Problems
52. Proof by Cases
To prove a conditional statement of the form:
Use the tautology
Each of the implications is a case.
53. Proof by Cases
Example: Let a @ b = max{a, b} = a if a ≥ b, otherwise
a @ b = max{a, b} = b.
Show that for all real numbers a, b, c
(a @b) @ c = a @ (b @ c)
(This means the operation @ is associative.)
Proof: Let a, b, and c be arbitrary real numbers.
Then one of the following 6 cases must hold.
1. a ≥ b ≥ c
2. a ≥ c ≥ b
3. b ≥ a ≥c
4. b ≥ c ≥a
5. c ≥ a ≥ b
6. c ≥ b ≥ a Continued on next slide
54. Proof by Cases
Case 1: a ≥ b ≥ c
(a @ b) = a, a @ c = a, b @ c = b
Hence (a @ b) @ c = a = a @ (b @ c)
Therefore the equality holds for the first case.
A complete proof requires that the equality be shown
to hold for all 6 cases. But the proofs of the
remaining cases are similar. Try them.
55. Without Loss of Generality
Example: Show that if x and y are integers and both x∙y and x+y are even,
then both x and y are even.
Proof: Use a proof by contraposition. Suppose x and y are not both even.
Then, one or both are odd. Without loss of generality, assume that x is odd.
Then x = 2m + 1 for some integer m.
Case 1: y is even. Then y = 2n for some integer n, so
x + y = (2m + 1) + 2n = 2(m + n) + 1 is odd.
Case 2: y is odd. Then y = 2n + 1 for some integer n, so
x ∙ y = (2m + 1) (2n + 1) = 2(2m ∙ n +m + n) + 1 is odd.
We only cover the case where x is odd because the case where y is odd is
similar. The use phrase without loss of generality (WLOG) indicates this.
56. Existence Proofs
Proof of theorems of the form .
Constructive existence proof:
Find an explicit value of c, for which P(c) is true.
Then is true by Existential Generalization (EG).
Example: Show that there is a positive integer that can be
written as the sum of cubes of positive integers in two
different ways:
Proof: 1729 is such a number since
1729 = 103 + 93 = 123 + 13
Godfrey Harold Hardy
(1877-1947)
Srinivasa Ramanujan
(1887-1920)
57. Nonconstructive Existence Proofs
In a nonconstructive existence proof, we assume no c
exists which makes P(c) true and derive a
contradiction.
Example: Show that there exist irrational numbers x
and y such that xy is rational.
Proof: We know that √2 is irrational. Consider the
number √2 √2 . If it is rational, we have two irrational
numbers x and y with xy rational, namely x = √2
and y = √2. But if √2 √2 is irrational,
then we can let x = √2 √2 and y = √2 so that xy
= (√2 √2 )√2 = √2 (√2 √2) = √2 2 = 2.
58. Counterexamples
Recall .
To establish that is true (or is false)
find a c such that P(c) is true or P(c) is false.
In this case c is called a counterexample to the
assertion .
Example: “Every positive integer is the sum of the
squares of 3 integers.” The integer 7 is a
counterexample. So the claim is false.
59. Uniqueness Proofs
Some theorems asset the existence of a unique element with a
particular property, !x P(x). The two parts of a uniqueness proof
are
Existence: We show that an element x with the property exists.
Uniqueness: We show that if y≠x, then y does not have the property.
Example: Show that if a and b are real numbers and a ≠0, then
there is a unique real number r such that ar + b = 0.
Solution:
Existence: The real number r = −b/a is a solution of ar + b = 0
because a(−b/a) + b = −b + b =0.
Uniqueness: Suppose that s is a real number such that as + b = 0.
Then ar + b = as + b, where r = −b/a. Subtracting b from both
sides and dividing by a shows that r = s.
60. Proof Strategies for proving p → q
Choose a method.
1. First try a direct method of proof.
2. If this does not work, try an indirect method (e.g., try to
prove the contrapositive).
For whichever method you are trying, choose a strategy.
1. First try forward reasoning. Start with the axioms and
known theorems and construct a sequence of steps that end
in the conclusion. Start with p and prove q, or start with ¬q
and prove ¬p.
2. If this doesn’t work, try backward reasoning. When trying to
prove q, find a statement p that we can prove with the
property p → q.
61. Backward Reasoning
Example: Suppose that two people play a game taking turns removing, 1, 2, or 3 stones at
a time from a pile that begins with 15 stones. The person who removes the last stone wins
the game. Show that the first player can win the game no matter what the second player
does.
Proof: Let n be the last step of the game.
Step n: Player1 can win if the pile contains 1,2, or 3 stones.
Step n-1: Player2 will have to leave such a pile if the pile that he/she is faced with has 4
stones.
Step n-2: Player1 can leave 4 stones when there are 5,6, or 7 stones left at the beginning of
his/her turn.
Step n-3: Player2 must leave such a pile, if there are 8 stones .
Step n-4: Player1 has to have a pile with 9,10, or 11 stones to ensure that there are 8 left.
Step n-5: Player2 needs to be faced with 12 stones to be forced to leave 9,10, or 11.
Step n-6: Player1 can leave 12 stones by removing 3 stones.
Now reasoning forward, the first player can ensure a win by removing 3 stones and leaving
12.
62. Universally Quantified Assertions
To prove theorems of the form ,assume x is an
arbitrary member of the domain and show that P(x)
must be true. Using UG it follows that .
Example: An integer x is even if and only if x2 is even.
Solution: The quantified assertion is
x [x is even x2 is even]
We assume x is arbitrary.
Recall that is equivalent to
So, we have two cases to consider. These are
considered in turn.
Continued on next slide
63. Universally Quantified Assertions
Case 1. We show that if x is even then x2 is even using
a direct proof (the only if part or necessity).
If x is even then x = 2k for some integer k.
Hence x2 = 4k2 = 2(2k2 ) which is even since it is an
integer divisible by 2.
This completes the proof of case 1.
Case 2 on next slide
64. Universally Quantified Assertions
Case 2. We show that if x2 is even then x must be even (the
if part or sufficiency). We use a proof by contraposition.
Assume x is not even and then show that x2 is not even.
If x is not even then it must be odd. So, x = 2k + 1 for some
k. Then x2 = (2k + 1)2 = 4k2 + 4k + 1 = 2(2k2 + 2k) + 1
which is odd and hence not even. This completes the proof
of case 2.
Since x was arbitrary, the result follows by UG.
Therefore we have shown that x is even if and only if x2 is
even.
65. Proof and Disproof: Tilings
Example 1: Can we tile the standard checkerboard
using dominos?
Solution: Yes! One example provides a constructive
existence proof.
The Standard Checkerboard
Two Dominoes
One Possible Solution
66. Tilings
Example 2: Can we tile a checkerboard obtained by
removing one of the four corner squares of a standard
checkerboard?
Solution:
Our checkerboard has 64 − 1 = 63 squares.
Since each domino has two squares, a board with a
tiling must have an even number of squares.
The number 63 is not even.
We have a contradiction.
67. Tilings
Example 3: Can we tile a board obtained by removing
both the upper left and the lower right squares of a
standard checkerboard?
Nonstandard Checkerboard Dominoes
Continued on next slide
68. Tilings
Solution:
There are 62 squares in this board.
To tile it we need 31 dominos.
Key fact: Each domino covers one black and one white
square.
Therefore the tiling covers 31 black squares and 31
white squares.
Our board has either 30 black squares and 32 white
squares or 32 black squares and 30 white squares.
Contradiction!
69. The Role of Open Problems
Unsolved problems have motivated much work in
mathematics. Fermat’s Last Theorem was conjectured
more than 300 years ago. It has only recently been
finally solved.
Fermat’s Last Theorem: The equation xn + yn = zn
has no solutions in integers x, y, and z, with xyz≠0
whenever n is an integer with n > 2.
A proof was found by Andrew Wiles in the 1990s.
70. An Open Problem
The 3x + 1 Conjecture: Let T be the transformation
that sends an even integer x to x/2 and an odd integer
x to 3x + 1. For all positive integers x, when we
repeatedly apply the transformation T, we will
eventually reach the integer 1.
For example, starting with x = 13:
T(13) = 3∙13 + 1 = 40, T(40) = 40/2 = 20, T(20) = 20/2 = 10,
T(10) = 10/2 = 5, T(5) = 3∙5 + 1 = 16,T(16) = 16/2 = 8,
T(8) = 8/2 = 4, T(4) = 4/2 = 2, T(2) = 2/2 = 1
The conjecture has been verified using computers up
to 5.6 ∙ 1013 .
71. Additional Proof Methods
Later we will see many other proof methods:
Mathematical induction, which is a useful method for
proving statements of the form n P(n), where the
domain consists of all positive integers.
Structural induction, which can be used to prove such
results about recursively defined sets.
Cantor diagonalization is used to prove results about the
size of infinite sets.
Combinatorial proofs use counting arguments.