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Logical Structures in Natural Language: Propositional Logic II (Tableaux) Raffaella Bernardi Universit` a degli Studi di Trento e-mail: bernardi@disi.unitn.it Contents First Last Prev Next Contents 1 What we have said last time . .


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Logical Structures in Natural Language: Propositional Logic II (Tableaux)

Raffaella Bernardi

Universit` a degli Studi di Trento e-mail: bernardi@disi.unitn.it

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Contents

1 What we have said last time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2 Remind: Propositional Logic: Basic Ideas . . . . . . . . . . . . . . . . . . . . 4 3 Remind: Language of Propositional Logic . . . . . . . . . . . . . . . . . . . . 5 4 Reminder: From English to Propositional Logic . . . . . . . . . . . . . . . 6 5 Reminder: Semantics: Intuition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 6 Reminder: Interpretation Function . . . . . . . . . . . . . . . . . . . . . . . . . . 8 7 Reminder: Truth Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 8 Reminder: Model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 9 Tautologies and Contradictions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 10 Reasoning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 11 Example of argumentations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 12 Reminder: exercises . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 13 Summary of key points. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 14 A formula: Tautology, Contradiction, Satisfiable, Falsifiable . . . . . 18 14.1 Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 15 An argumentation: Validity. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 15.1 Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

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15.2 Exercises . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 16 Counter-example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23 17 NEW: Tableaux Calculus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 17.1 Tableaux: the calculus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 18 Heuristics and Exercises . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 18.1 Sets of formulas. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 19 Formula . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 20 Done to be done and Home work . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

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1. What we have said last time

  • Logic

– Language: syntax, semantics. – Reasoning

  • Semantics

– Meaning of a sentence = Truth value

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1. What we have said last time

  • Logic

– Language: syntax, semantics. – Reasoning

  • Semantics

– Meaning of a sentence = Truth value – Compositional meaning: truth-functional connectives

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1. What we have said last time

  • Logic

– Language: syntax, semantics. – Reasoning

  • Semantics

– Meaning of a sentence = Truth value – Compositional meaning: truth-functional connectives – Interpretation Function: FORM → {true, false}

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1. What we have said last time

  • Logic

– Language: syntax, semantics. – Reasoning

  • Semantics

– Meaning of a sentence = Truth value – Compositional meaning: truth-functional connectives – Interpretation Function: FORM → {true, false}

  • Reasoning: Premises |

= α iff W(Premises) ⊆ W(α) Today we look more into Propositional Logic (PL)

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2. Remind: Propositional Logic: Basic Ideas

Statements: The elementary building blocks of propositional logic are atomic statements that cannot be decomposed any further: propositions.

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2. Remind: Propositional Logic: Basic Ideas

Statements: The elementary building blocks of propositional logic are atomic statements that cannot be decomposed any further: propositions. E.g.,

  • “The box is red”
  • “The proof of the pudding is in the eating”
  • “It is raining”

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2. Remind: Propositional Logic: Basic Ideas

Statements: The elementary building blocks of propositional logic are atomic statements that cannot be decomposed any further: propositions. E.g.,

  • “The box is red”
  • “The proof of the pudding is in the eating”
  • “It is raining”

and logical connectives “and”, “or”, “not”, by which we can build propositional formulas.

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3. Remind: Language of Propositional Logic

Alphabet The alphabet of PL consists of:

  • A countable set of propositional symbols: p, q, r, . . .
  • The logical connectives : ¬ (NOT), ∧ (AND), ∨ (OR), → (implication), ↔

(double implication).

  • Parenthesis: (,) (they are used to disambiguate the language)

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3. Remind: Language of Propositional Logic

Alphabet The alphabet of PL consists of:

  • A countable set of propositional symbols: p, q, r, . . .
  • The logical connectives : ¬ (NOT), ∧ (AND), ∨ (OR), → (implication), ↔

(double implication).

  • Parenthesis: (,) (they are used to disambiguate the language)

Well formed formulas (wff) They are defined recursively

  • 1. a propositional symbol is a wff:
  • 2. if A is a wff then also ¬A is a wff
  • 3. if A and B are wff then also (A ∧ B), (A ∨ B), (A → B) and (A → B) are wff
  • 4. nothing else is a wff.

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4. Reminder: From English to Propositional Logic

  • Eg. If you don’t sleep then you will be tired.

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4. Reminder: From English to Propositional Logic

  • Eg. If you don’t sleep then you will be tired.

Keys: p = you sleep, q= you will be tired. Formula: ¬p → q.

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4. Reminder: From English to Propositional Logic

  • Eg. If you don’t sleep then you will be tired.

Keys: p = you sleep, q= you will be tired. Formula: ¬p → q. Exercise I:

  • 1. If it rains while the sun shines, a rainbow will appear
  • 2. Charles comes if Elsa does and the other way around
  • 3. If I have lost if I cannot make a move, then I have lost.

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4. Reminder: From English to Propositional Logic

  • Eg. If you don’t sleep then you will be tired.

Keys: p = you sleep, q= you will be tired. Formula: ¬p → q. Exercise I:

  • 1. If it rains while the sun shines, a rainbow will appear
  • 2. Charles comes if Elsa does and the other way around
  • 3. If I have lost if I cannot make a move, then I have lost.
  • 1. (rain ∧ sun) → rainbow
  • 2. elsa ↔ charles
  • 3. (¬move → lost) → lost

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4. Reminder: From English to Propositional Logic

  • Eg. If you don’t sleep then you will be tired.

Keys: p = you sleep, q= you will be tired. Formula: ¬p → q. Exercise I:

  • 1. If it rains while the sun shines, a rainbow will appear
  • 2. Charles comes if Elsa does and the other way around
  • 3. If I have lost if I cannot make a move, then I have lost.
  • 1. (rain ∧ sun) → rainbow
  • 2. elsa ↔ charles
  • 3. (¬move → lost) → lost

Use: http://www.earlham.edu/~peters/courses/log/transtip.htm

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5. Reminder: Semantics: Intuition

  • Atomic propositions can be true T or false F.

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5. Reminder: Semantics: Intuition

  • Atomic propositions can be true T or false F.
  • The truth value of formulas is determined by the truth values of the atoms

(truth value assignment or interpretation).

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5. Reminder: Semantics: Intuition

  • Atomic propositions can be true T or false F.
  • The truth value of formulas is determined by the truth values of the atoms

(truth value assignment or interpretation). Example: (a∨b)∧c: If a and b are false and c is true, then the formula is not true.

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5. Reminder: Semantics: Intuition

  • Atomic propositions can be true T or false F.
  • The truth value of formulas is determined by the truth values of the atoms

(truth value assignment or interpretation). Example: (a∨b)∧c: If a and b are false and c is true, then the formula is not true.

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6. Reminder: Interpretation Function

The interpretation function, denoted by I, can assign true (T) or false (F) to the atomic formulas; for the complex formula they obey the following conditions. Given the formulas P, Q of L:

  • a. I(¬P) = T iff I(P) = F

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6. Reminder: Interpretation Function

The interpretation function, denoted by I, can assign true (T) or false (F) to the atomic formulas; for the complex formula they obey the following conditions. Given the formulas P, Q of L:

  • a. I(¬P) = T iff I(P) = F
  • b. I(P ∧ Q) = T iff I(P) = T e I(Q) = T

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6. Reminder: Interpretation Function

The interpretation function, denoted by I, can assign true (T) or false (F) to the atomic formulas; for the complex formula they obey the following conditions. Given the formulas P, Q of L:

  • a. I(¬P) = T iff I(P) = F
  • b. I(P ∧ Q) = T iff I(P) = T e I(Q) = T
  • c. I(P ∨ Q) = F iff I(P) = F e I(Q) = F

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6. Reminder: Interpretation Function

The interpretation function, denoted by I, can assign true (T) or false (F) to the atomic formulas; for the complex formula they obey the following conditions. Given the formulas P, Q of L:

  • a. I(¬P) = T iff I(P) = F
  • b. I(P ∧ Q) = T iff I(P) = T e I(Q) = T
  • c. I(P ∨ Q) = F iff I(P) = F e I(Q) = F
  • d. I(P → Q) = F iff I(P) = T e I(Q) = F

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6. Reminder: Interpretation Function

The interpretation function, denoted by I, can assign true (T) or false (F) to the atomic formulas; for the complex formula they obey the following conditions. Given the formulas P, Q of L:

  • a. I(¬P) = T iff I(P) = F
  • b. I(P ∧ Q) = T iff I(P) = T e I(Q) = T
  • c. I(P ∨ Q) = F iff I(P) = F e I(Q) = F
  • d. I(P → Q) = F iff I(P) = T e I(Q) = F
  • e. I(P ↔ Q) = F iff I(P) = I(Q)

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7. Reminder: Truth Tables

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7. Reminder: Truth Tables

φ ¬φ I1 T F I2 F T (1)

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7. Reminder: Truth Tables

φ ¬φ I1 T F I2 F T (1) φ ψ φ ∧ ψ I1 T T T I2 T F F I3 F T F I4 F F F (1)

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7. Reminder: Truth Tables

φ ¬φ I1 T F I2 F T (1) φ ψ φ ∧ ψ I1 T T T I2 T F F I3 F T F I4 F F F (1) φ ψ φ ∨ ψ I1 T T T I2 T F T I3 F T T I4 F F F (1)

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7. Reminder: Truth Tables

φ ¬φ I1 T F I2 F T (1) φ ψ φ ∧ ψ I1 T T T I2 T F F I3 F T F I4 F F F (1) φ ψ φ ∨ ψ I1 T T T I2 T F T I3 F T T I4 F F F (1) φ ψ φ → ψ I1 T T T I2 T F F I3 F T T I4 F F T (1)

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8. Reminder: Model

A model consists of two pieces of information:

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8. Reminder: Model

A model consists of two pieces of information:

  • which collection of atomic propositions we are talking about (domain, D),

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8. Reminder: Model

A model consists of two pieces of information:

  • which collection of atomic propositions we are talking about (domain, D),
  • and for each formula which is the appropriate semantic value, this is done by

means of a function called interpretation function (I).

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8. Reminder: Model

A model consists of two pieces of information:

  • which collection of atomic propositions we are talking about (domain, D),
  • and for each formula which is the appropriate semantic value, this is done by

means of a function called interpretation function (I). Thus a model M is a pair: (D, I).

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8. Reminder: Model

A model consists of two pieces of information:

  • which collection of atomic propositions we are talking about (domain, D),
  • and for each formula which is the appropriate semantic value, this is done by

means of a function called interpretation function (I). Thus a model M is a pair: (D, I).

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9. Tautologies and Contradictions

Build the truth table of p ∧ ¬p.

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9. Tautologies and Contradictions

Build the truth table of p ∧ ¬p. It’s a contradiction: always false.

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9. Tautologies and Contradictions

Build the truth table of p ∧ ¬p. It’s a contradiction: always false. Build the truth table of (p → q) ∨ (q → p).

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9. Tautologies and Contradictions

Build the truth table of p ∧ ¬p. It’s a contradiction: always false. Build the truth table of (p → q) ∨ (q → p). It’s a tautology: always true. A formula P is:

  • satisfiabiliy if there is at least an interpretation I such that I(P) = True

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10. Reasoning

P1, . . . , Pn | = C a valid deductive argumentation is such that its conclusion cannot be false when the premises are true. In other words, there is no interpretation for which the conclusion is false and the premises are true. W(Premise), the set of interpretations for which the premises are all true, and W(C) the set of interpretations for which the conclusion is true: W(Premises) ⊆ W(C) The premises entail α iff α is true for all the interpretations for which all the premises are true.

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10. Reasoning

P1, . . . , Pn | = C a valid deductive argumentation is such that its conclusion cannot be false when the premises are true. In other words, there is no interpretation for which the conclusion is false and the premises are true. W(Premise), the set of interpretations for which the premises are all true, and W(C) the set of interpretations for which the conclusion is true: W(Premises) ⊆ W(C) The premises entail α iff α is true for all the interpretations for which all the premises are true.

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11. Example of argumentations

Today is Monday or today is Thursday P v Q Today is not Monday not P ================= ===== Today is Thursday Q

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11. Example of argumentations

Today is Monday or today is Thursday P v Q Today is not Monday not P ================= ===== Today is Thursday Q If today is Thursday, then today I’ve a lecture Q --> R Today is Thursday Q =============== ======= Today I’ve a lecture R

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11. Example of argumentations

Today is Monday or today is Thursday P v Q Today is not Monday not P ================= ===== Today is Thursday Q If today is Thursday, then today I’ve a lecture Q --> R Today is Thursday Q =============== ======= Today I’ve a lecture R P ∨ Q, ¬P | = Q Q → R, Q | = R

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11. Example of argumentations

Today is Monday or today is Thursday P v Q Today is not Monday not P ================= ===== Today is Thursday Q If today is Thursday, then today I’ve a lecture Q --> R Today is Thursday Q =============== ======= Today I’ve a lecture R P ∨ Q, ¬P | = Q Q → R, Q | = R

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Try to build truth tables to verify: P ∨ Q, ¬P | = Q P Q P ∨ Q ¬P Q I1 T T T F T I2 T F T F F I3 F T T T T I4 F F F T F W(Premesse) ⊆ W(Q)

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Try to build truth tables to verify: P ∨ Q, ¬P | = Q P Q P ∨ Q ¬P Q I1 T T T F T I2 T F T F F I3 F T T T T I4 F F F T F W(Premesse) ⊆ W(Q) {I3} ⊆ {I1, I3}

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12. Reminder: exercises

Build the truth tables for the following formulas and decide whether they are satis- fiable, or a tautology or a contradiction.

  • (¬A → B) ∧ (¬A ∨ B)
  • P → (Q ∨ ¬R)

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Build the truth tables for the following entailments and decide whether they are valid

  • 1. P ∨ Q |

= Q

  • 2. P → Q, Q → R |

= P → R

  • 3. P → Q, Q |

= P

  • 4. P → Q |

= ¬(Q → P)

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13. Summary of key points.

  • Tomorrow bring the solutions for the exercises.
  • Today key concepts

– Syntax of PL: atomic vs. complex formulas – Semantics of PL: truth tables – Formalization of simple arguments – Interpretation function – Domain – Model – Entailment – Satisfiability

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14. A formula: Tautology, Contradiction, Satisfi- able, Falsifiable

Recall, a formula P is:

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14. A formula: Tautology, Contradiction, Satisfi- able, Falsifiable

Recall, a formula P is:

  • tautology if for all the interpretations I, I(P) = True (it’s always true)
  • contradiction if for all the interpretations I, I(P) = False (is always false)

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14. A formula: Tautology, Contradiction, Satisfi- able, Falsifiable

Recall, a formula P is:

  • tautology if for all the interpretations I, I(P) = True (it’s always true)
  • contradiction if for all the interpretations I, I(P) = False (is always false)

A formula P is:

  • satisfiabiliy if there is at least an interpretation I such that I(P) = True
  • falsifiable if there is at least an interpretation I such that I(P) = False

A formula that is false in all interpretation is also called unsatisfiable.

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14.1. Example

P ¬P ¬P ∨ P I1 T F T I2 F T T ¬P ∨ P is a tautology.

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15. An argumentation: Validity

{P1, . . . , Pn} | = C a valid deductive argumentation is such that its conclusion cannot be false when the premises are true. In other words, there is no interpretation for which the conclusion is false and the premises are true. W(Premise), the set of interpretations for which the premises are all true, and W(C) the set of interpretations for which the conclusion is true: W(Premises) ⊆ W(C)

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15.1. Example

P Q P ∨ Q ¬P Q I1 T T T F T I2 T F T F F I3 F T T T T I4 F F F T F W(Premesse) ⊆ W(Q)

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15.1. Example

P Q P ∨ Q ¬P Q I1 T T T F T I2 T F T F F I3 F T T T T I4 F F F T F W(Premesse) ⊆ W(Q) {I3} ⊆ {I1, I3}

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15.2. Exercises

Check whether the following arguments are valid: If the temperature and air pressure remained constant, there was no rain. The temperature did remain constant. Therefore, if there was rain then the air pressure did not remain constant. If Paul lives in Dublin, he lives in Ireland. Paul lives in Ireland. Therefore Paul lives in Dublin. (i) Give the keys of your formalization using PL; (ii) represent the argument formally, and (iii) Apply the truth table method to prove or disprove the validity of the argument.

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16. Counter-example

Counterexample an interpretation in which the reasoning does not hold. In other words, an interpretation such that the premises are true and the conclusion is false. Exercise: together Take the previous exercise and build a counter-example if the argumentation is not valid If the temperature and air pressure remained constant, there was no rain. The temperature did remain constant. Therefore, if there was rain then the air pressure did not remain constant. If Paul lives in Dublin, he lives in Ireland. Paul lives in Ireland. Therefore Paul lives in Dublin. Exercises: alone See printed paper (pl3)

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17. NEW: Tableaux Calculus

  • The Tableaux Calculus is a decision procedure solving the problem of satisfia-

bility.

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17. NEW: Tableaux Calculus

  • The Tableaux Calculus is a decision procedure solving the problem of satisfia-

bility.

  • If a formula is satisfiable, the procedure will constructively exhibit an interpre-

tation in which the formula is true.

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17. NEW: Tableaux Calculus

  • The Tableaux Calculus is a decision procedure solving the problem of satisfia-

bility.

  • If a formula is satisfiable, the procedure will constructively exhibit an interpre-

tation in which the formula is true.

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17.1. Tableaux: the calculus

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17.1. Tableaux: the calculus

A ∧ B A B

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17.1. Tableaux: the calculus

A ∧ B A B A ∨ B

  • A

B

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17.1. Tableaux: the calculus

A ∧ B A B A ∨ B

  • A

B A → B

  • ¬A

B

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17.1. Tableaux: the calculus

A ∧ B A B A ∨ B

  • A

B A → B

  • ¬A

B A ↔ B

  • A ∧ B

¬A ∧ ¬B

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17.1. Tableaux: the calculus

A ∧ B A B A ∨ B

  • A

B A → B

  • ¬A

B A ↔ B

  • A ∧ B

¬A ∧ ¬B ¬¬A A

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17.1. Tableaux: the calculus

A ∧ B A B A ∨ B

  • A

B A → B

  • ¬A

B A ↔ B

  • A ∧ B

¬A ∧ ¬B ¬¬A A ¬(A ∧ B)

  • ¬A

¬B

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17.1. Tableaux: the calculus

A ∧ B A B A ∨ B

  • A

B A → B

  • ¬A

B A ↔ B

  • A ∧ B

¬A ∧ ¬B ¬¬A A ¬(A ∧ B)

  • ¬A

¬B ¬(A ∨ B) ¬A ¬B

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17.1. Tableaux: the calculus

A ∧ B A B A ∨ B

  • A

B A → B

  • ¬A

B A ↔ B

  • A ∧ B

¬A ∧ ¬B ¬¬A A ¬(A ∧ B)

  • ¬A

¬B ¬(A ∨ B) ¬A ¬B ¬(A → B) A ¬B

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17.1. Tableaux: the calculus

A ∧ B A B A ∨ B

  • A

B A → B

  • ¬A

B A ↔ B

  • A ∧ B

¬A ∧ ¬B ¬¬A A ¬(A ∧ B)

  • ¬A

¬B ¬(A ∨ B) ¬A ¬B ¬(A → B) A ¬B ¬(A ↔ B)

  • A ∧ ¬B

¬A ∧ B

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SLIDE 74

18. Heuristics and Exercises

Apply non-branching rules before branching rules.

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SLIDE 75

18. Heuristics and Exercises

Apply non-branching rules before branching rules. Exercises Take the exercises done so far using truth tables and prove by means of tableaux whether the formula is satisfiable.

  • A ∧ (B ∧ ¬A)
  • (A → B) → ¬B
  • A → (B → A)
  • (B → A) → A
  • (¬A → B) ∧ (¬A ∨ B)
  • A → (B ∨ ¬C)

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SLIDE 76

18.1. Sets of formulas

Determine whether the following sets of logical forms are satisfiable by means of truth tables first and then by tableaux method; in other words, you are asked to check whether there is at least an interpretation in which all the formulas in the set are true. {¬B → B, ¬(A → B), ¬A ∨ ¬B} {¬A ∨ B, ¬(B ∧ ¬C), C → D, ¬(¬A ∨ D)}

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SLIDE 77

19. Formula

You are asked to prove whether ψ is a tautology by means of tableaux.

  • If all branches of your tableaux are open, what do you conclude?

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SLIDE 78

19. Formula

You are asked to prove whether ψ is a tautology by means of tableaux.

  • If all branches of your tableaux are open, what do you conclude?

ψ is satisfiable.

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SLIDE 79

19. Formula

You are asked to prove whether ψ is a tautology by means of tableaux.

  • If all branches of your tableaux are open, what do you conclude?

ψ is satisfiable. Are you sure you cannot give a stronger answer, i.e. are you sure ψ is not a tautology?

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SLIDE 80

19. Formula

You are asked to prove whether ψ is a tautology by means of tableaux.

  • If all branches of your tableaux are open, what do you conclude?

ψ is satisfiable. Are you sure you cannot give a stronger answer, i.e. are you sure ψ is not a tautology? In order to check whether ψ is a tautology you have to look at ¬ψ.

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SLIDE 81

19. Formula

You are asked to prove whether ψ is a tautology by means of tableaux.

  • If all branches of your tableaux are open, what do you conclude?

ψ is satisfiable. Are you sure you cannot give a stronger answer, i.e. are you sure ψ is not a tautology? In order to check whether ψ is a tautology you have to look at ¬ψ. If ¬ψ is unsatisfiable then ψ is also a tautology.

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SLIDE 82

19. Formula

You are asked to prove whether ψ is a tautology by means of tableaux.

  • If all branches of your tableaux are open, what do you conclude?

ψ is satisfiable. Are you sure you cannot give a stronger answer, i.e. are you sure ψ is not a tautology? In order to check whether ψ is a tautology you have to look at ¬ψ. If ¬ψ is unsatisfiable then ψ is also a tautology.

  • If all branches close: ψ is unsatisfiable.

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SLIDE 83

19. Formula

You are asked to prove whether ψ is a tautology by means of tableaux.

  • If all branches of your tableaux are open, what do you conclude?

ψ is satisfiable. Are you sure you cannot give a stronger answer, i.e. are you sure ψ is not a tautology? In order to check whether ψ is a tautology you have to look at ¬ψ. If ¬ψ is unsatisfiable then ψ is also a tautology.

  • If all branches close: ψ is unsatisfiable.

Can you make a stronger claim?

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SLIDE 84

19. Formula

You are asked to prove whether ψ is a tautology by means of tableaux.

  • If all branches of your tableaux are open, what do you conclude?

ψ is satisfiable. Are you sure you cannot give a stronger answer, i.e. are you sure ψ is not a tautology? In order to check whether ψ is a tautology you have to look at ¬ψ. If ¬ψ is unsatisfiable then ψ is also a tautology.

  • If all branches close: ψ is unsatisfiable.

Can you make a stronger claim? No this is already a strong result, there is no need to look at ¬ψ. More on this next time.

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SLIDE 85

20. Done to be done and Home work

Today we have looked at:

  • Recalled: Prove whether a formula is satisfiable by means of Truth Tables
  • Recalled: Prove whether an entailment is valid by means of Truth Tables.
  • Prove whether a formula is satisfiable by means of Tableaux.

Next time we will look at how to prove whether

  • a set of formulas is satisfiable by means of Tableaux.
  • a formula is a tautology by means of Tableaux
  • an entailment is valid by means of Tableaux.

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