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1.3. Notes for Chapter 3: Conjunctions, Disjunctions, and Negations

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16 Symbolic Logic Study Guide: Class Notes 1.3. Notes for Chapter 3: Conjunctions, Disjunctions, and Negations 1.3.1. Introduction to Conjunctions, Disjunctions, and Negations (3.1, 3.2, 3.3, and 3.4 of the Text) 1. Introduction 1.1 Moving from atomic sentences to compound sentences one single predicate Simple sentences: no truth-functional connectives. Sentences More than one predicate Compound sentences Two or more simple sentences connected by some truth- functional connectives. For example: John is a student and Joe is a teacher. John or Joe is a student = John is a student or Joe is a student. If John is a student, then Joe is a teacher. John is not a student. 1.2 Truth-functional vs. Non-truth-functional sentences. Definition: a compound sentence is truth-functional iff the truth-value of the sentence is fully determined by the truth-value of its component simple sentences. Then the connectives connected component sentences of a truth-functional sentence is truth- functional connectives. They are: conjunction, disjunction, negation, and conditional. For example, Truth-functional sentences: John is a student and Joe is a teacher. (False) True False If John is a student, then Joe is a teacher. (False) True False Symbolic Logic Study Guide: Class Notes 17 Non-truth-functional sentences: John loves Kathy because he kisses her. (True or False) True I believe that Pat is on the mat (propositional attitude). (True or False) True 2. Syntax of truth-functional connectives In English In FOL Conjunction and, but, however, although, ∧ / & nevertheless, moreover, in additions, , Disjunction or, either...or..., at least one of two..., unless ∨ Negation not, be hardly, unhappy, impossible, incomplete ¬ Attention: two senses of disjunction In exclusive sense: exactly one alternative (at least one and at most one alternative) Disjunction In inclusive sense: at least one alternative (and could be both) For example: Waitress: “You can have ice cream or a cake as desert” (but not both). Alice and Katy’s father: “John, you can marry either Alice or Kathy” (but not both). Professor: “Joe, you can take either ethics or human nature course to fulfill your philosophy requirement” (sure you can take both if you like). In FOL, we define “OR” in inclusive sense only. 3. Semantics of truth-functional connectives 3.1 Truth-table definitions: Suppose that P and Q here represent any sentence (either simple or compound sentences). We can define the truth-value of a compound sentence consisting of P and Q as follows: P Q P ∧ Q P ∨ Q ¬ P T T T T F T F F T F F T F T T F F F F T 18 Symbolic Logic Study Guide: Class Notes 3.2 How to determine the truth value of a sentence? (1) If the truth-values of component sentences of a compound sentence are given: From inside to outside! (when you determine the truth value of a sentence based on a Tarski’s World). Primary connective (P ∧ Q) ∧ (Q ∨ R) T F F F F T T ¬ (P ∧ Q) ∧ (R ∨ P) T F F T T T T F (2) If the truth value of a compound sentence is given: from outside to inside! (when you play the game to see your truth commitments) (P ∧ Q) ∧ (Q ∨ R), therefore, P is true, Q is true, and R could be true or false. T T T ¬ (P ∧ Q) ∧ (R ∨ P) F In this case, there are four possible truth values: • R is false and P is false, and Q could be true or false. OR • P is true and Q is true, and R could be either true or false. 4. Correct use of parentheses (P ∧ Q) ∨ R P ∧ Q ∨ R (WRONG!) Which one??? P ∧ (Q ∨ R) Conventions: • “¬” always apply to the smallest unit right after it: ¬ R ∨ (P ∨ Q) ¬ (R ∨ (P ∨ Q)) ¬ (R ∨ P) ∨ Q • R ∨ P ∨ Q Okay!!! • P ∧ Q ∧ R Okay!!! Symbolic Logic Study Guide: Class Notes 19 1.3.2. Logical Equivalency (3.5 of the Text) 1. Definition: Two sentences are logically equivalent iff they have same truth value in exactly the same circumstances (under any possible interpretation / in any possible world). Illustrations: 1.1 In the language of the Tarski’s World (with fixed interpretation) a is to one side or other of cube b, but is in front of dodecahedron c. Suppose that you have two different translations of the above English sentence as follows: (a) [Cube(b) ∧ ( LeftOf(a, b) ∨ RightOf(a, b) ) ] ∧ [Dodec(c) ∧ FrontOf (a, c)] (b) [ (Cube(b) ∧ LeftOf(a, b)) ∨ (Cube(b) ∧ RightOf(a, b)) ] ∧ [Dodec(c) ∧ FrontOf (a, c)] Are sentence (a) and (b) logically equivalent? To determine this, you need to see whether they always have the same truth value in any Tarski’s world. If they always have the same truth value in any Tarski’s world, then they are logically equivalent (Question: How can you do this???). If they do not have the same truth value in one Tarski’s world, then they are not logically equivalent (an counterexample). 1.2 In any formal language (a) ¬ (P(a) ∧ Q(a)) (b) ¬ P(a) ∧ ¬ Q(a) Are the above sentences in FOL logically equivalent? To find out, let us give a possible interpretation to the predicates and names under considerations. Suppose: P(x): x is a student. Q(x): x is a female. a: Sean Under this interpretation, sentence (a) means that it is not the case that Sean is a female student or Sean is not a female student (but Sean may be a student). Sentence (b) says that Sean is not a female, and Sean is not a student either. Suppose further that Sean is a male student in a possible world. Then under the above interpretation and in the above circumstance, sentence (a) is true but sentence (b) is false. In conclusion, sentences (a) and (b) are not logically equivalent (since we have found one possible world in which they do not have the same truth value). 2. How to test logical equivalency? There are many different formal methods to test for logical equivalency. We will only introduce two of them at this stage. 20 Symbolic Logic Study Guide: Class Notes 2.1 Truth-table method Make a truth table for both sentences to be tested. If they have the same truth values at all rows, then they are logically equivalent. Otherwise they are not. P Q ¬ (P ∧ Q) ¬ P ∨ ¬ Q T T F F T F T T F T T T F F T T Conclusion: “¬ (P ∧ Q)” and “¬ P ∨ ¬ Q” are logically equivalent. That is, ¬ (P ∧ Q) ⇔ ¬ P∨ ¬ Q P Q ¬ (P ∧ Q) ¬ P ∧ ¬ Q T T F F T F T F F T T F counterexamples F F T T Conclusion: “¬ (P ∧ Q)” and “¬ P∧ ¬ Q” are not logically equivalent. 2.2 Rules of logical equivalency Rules: (1) Double negation: ¬¬ P ⇔ P (2) DeMorgan Rules: ¬ (P ∧ Q) ⇔ ¬ P ∨ ¬ Q ¬ (P ∨ Q) ⇔ ¬ P ∧ ¬ Q • Negation normal form: “¬” only applies to atomic sentences. (3) Idempotence: P ∧ P ⇔ P P ∨ P ⇔ P (4) Commutative rules: P ∧ Q ∧ R ⇔ R ∧ P ∧ Q P ∨ Q ∨ R ⇔ Q ∨ R ∨ P (5) Association rules: (P ∧ Q) ∧ R ⇔ P ∧ (Q ∧ R) P ∨ (Q ∨ R) ⇔ (P ∨ Q) ∨ R (6) Distribution rules: P ∧ (Q ∨ R) ⇔ (P ∧ Q) ∨ (P ∧ R) P ∨ (Q ∧ R) ⇔ (P ∨ Q) ∧ (P ∨ R) • Disjunctive normal form: disjunction of conjunction of literals. • Conjunctive normal form: conjunction of disjunction of literals. Symbolic Logic Study Guide: Class Notes 21 Examples: (1) Put ¬ [(A ∧ B) ∧ (C ∨ ¬ D)] into negation normal form. ¬ [(A ∧ B) ∧ (C ∨ ¬ D)] ⇔ ¬ (A ∧ B) ∨ ¬ (C ∨ ¬D) ⇔ (¬ A ∨ ¬ B) ∨ (¬C ∧ ¬¬ D) ⇔ (¬ A ∨ ¬ B) ∨ (¬C ∧ D) (2) Put (A ∨ B) ∧ C ∧ [¬ (¬B ∧ ¬ A) ∨ B] into negation normal form (A ∨ B) ∧ C ∧ [¬ (¬B ∧ ¬ A) ∨ B] ⇔ (A ∨ B) ∧ C ∧ [ (¬¬B ∨ ¬¬A) ∨ B] ⇔ (A ∨ B) ∧ C ∧ [( B ∨ A) ∨ B] ⇔ (A ∨ B) ∧ C ∧ ( B ∨ A ∨ B) ⇔ (A ∨ B) ∧ C ∧ (A ∨ B) ⇔ (A ∨ B) ∧ C (3) Put (A∨ B) ∧ (C ∨ D) into disjunctive normal form. (A∨ B) ∧ (C ∨ D) ⇔ [(A∨ B) ∧ C] ∨ [(A∨ B) ∧ D] ⇔ [(A ∧ C) ∨ (B ∧ C)] ∨ [(A ∧ D) ∨ (B ∧ D)] ⇔ (A ∧ C) ∨ (B ∧ C) ∨ (A ∧ D) ∨ (B ∧ D) (4) Prove that ¬ (A ∨ B) ∧ ¬ (B ∨ C) and ¬A ∧ ¬ B ∧ ¬ C are logically equivalent. Prove: ¬ (A ∨ B) ∧ ¬ (B ∨ C) ⇔ (¬A ∧¬B) ∧ (¬B ∧ ¬C) ⇔ ¬A ∧¬B ∧ ¬B ∧ ¬C ⇔ ¬A ∧ ¬ B ∧ ¬ C as desired. (5) Prove that (A ∨ B) ∧C ∧ ¬(¬ B ∧¬A) and (A∨B) ∧C are logically equivalent. Prove: (A ∨ B) ∧C ∧ ¬(¬ B ∧¬A) ⇔ (A ∨ B) ∧C ∧ (¬¬B ∨¬¬A) ⇔ (A ∨ B) ∧C ∧ (B ∨ A) ⇔ (A ∨ B) ∧C as desired! 22 Symbolic Logic Study Guide: Class Notes 1.3.3. Translation (3.6 of the Text) 1. A standard of a correct translation A (not the) logical symbolization of an English sentence is correct iff both are logically equivalent. 2. Tips for translations involving conjunctions, disjunctions and negations (1) Identify the primary connective of the original English sentence to be translated. Example: Both d and c are cubes; moreover neither of them is small. Primary (Cube(d) ∧ Cube(c)) ∧ (¬ Small(d) ∧ ¬ Small(c)) (2) Paraphrase, if necessary, the sentences to be translated before translation (as long as they are both logically equivalent). Example: The original sentence: Neither e nor a is to the right of c and to the left of b Rewrite the sentence as: “Neither e is to the right of c and to the left of b nor a is to the right of c and to the left of b.” “It is not the case that e is to the right of c and to the left of b AND it is not the case that a is to the right of c and to the left of b.” After the paraphrasing, translation is easy: ¬ [RightOfOf(e, c) ∧ LeftOf(e, b)] ∧ ¬[RightOf(a, c) ∧ LeftOf(a, b)] (3) A few common patterns of sentences • Exclusive sense of OR, P or Q (but not both): (P ∨ Q) ∧ ¬ (P ∧ Q) • Neither P not Q ⇔ It is not that either P or Q: ¬ P ∧ ¬ Q ⇔ ¬ (P ∨ Q) • P unless Q: P ∨ Q Symbolic Logic Study Guide: Class Notes 23 3.
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    Lecture Notes 1 Logic for Computer Science. Knowledge Representation and Reasoning. Lecture Notes for Computer Science Students Faculty EAIiIB-IEiT AGH Antoni Lig˛eza Other support material: http://home.agh.edu.pl/~ligeza https://ai.ia.agh.edu.pl/pl:dydaktyka:logic: start#logic_for_computer_science2020 c Antoni Lig˛eza:2020 Lecture Notes 2 Inference and Theorem Proving in Propositional Calculus • Tasks and Models of Automated Inference, • Theorem Proving models, • Some important Inference Rules, • Theorems of Deduction: 1 and 2, • Models of Theorem Proving, • Examples of Proofs, • The Resolution Method, • The Dual Resolution Method, • Logical Derivation, • The Semantic Tableau Method, • Constructive Theorem Proving: The Fitch System, • Example: The Unicorn, • Looking for Models: Towards SAT. c Antoni Lig˛eza Lecture Notes 3 Logic for KRR — Tasks and Tools • Theorem Proving — Verification of Logical Consequence: ∆ j= H; • Method of Theorem Proving: Automated Inference —- Derivation: ∆ ` H; • SAT (checking for models) — satisfiability: j=I H (if such I exists); • un-SAT verification — unsatisfiability: 6j=I H (for any I); • Tautology verification (completeness): j= H • Unsatisfiability verification 6j= H Two principal issues: • valid inference rules — checking: (∆ ` H) −! (∆ j= H) • complete inference rules — checking: (∆ j= H) −! (∆ ` H) c Antoni Lig˛eza Lecture Notes 4 Two Possible Fundamental Approaches: Checking of Interpretations versus Logical Inference Two basic approaches – reasoning paradigms: • systematic evaluation of possible interpretations — the 0-1 method; problem — combinatorial explosion; for n propositional variables we have 2n interpretations! • logical inference— derivation — with rules preserving logical conse- quence. Notation: formula H (a Hypothesis) is derivable from ∆ (a Knowledge Base; a set of domain axioms): ∆ ` H This means that there exists a sequence of applications of inference rules, such that H is mechanically derived from ∆.
  • Natural Deduction with Propositional Logic

    Natural Deduction with Propositional Logic

    Natural Deduction with Propositional Logic Introducing Natural Natural Deduction with Propositional Logic Deduction Ling 130: Formal Semantics Some basic rules without assumptions Rules with assumptions Spring 2018 Outline Natural Deduction with Propositional Logic Introducing 1 Introducing Natural Deduction Natural Deduction Some basic rules without assumptions 2 Some basic rules without assumptions Rules with assumptions 3 Rules with assumptions What is ND and what's so natural about it? Natural Deduction with Natural Deduction Propositional Logic A system of logical proofs in which assumptions are freely introduced but discharged under some conditions. Introducing Natural Deduction Introduced independently and simultaneously (1934) by Some basic Gerhard Gentzen and Stanis law Ja´skowski rules without assumptions Rules with assumptions The book & slides/handouts/HW represent two styles of one ND system: there are several. Introduced originally to capture the style of reasoning used by mathematicians in their proofs. Ancient antecedents Natural Deduction with Propositional Logic Aristotle's syllogistics can be interpreted in terms of inference rules and proofs from assumptions. Introducing Natural Deduction Some basic rules without assumptions Rules with Stoic logic includes a practical application of a ND assumptions theorem. ND rules and proofs Natural Deduction with Propositional There are at least two rules for each connective: Logic an introduction rule an elimination rule Introducing Natural The rules reflect the meanings (e.g. as represented by Deduction Some basic truth-tables) of the connectives. rules without assumptions Rules with Parts of each ND proof assumptions You should have four parts to each line of your ND proof: line number, the formula, justification for writing down that formula, the goal for that part of the proof.