artificial intelligence lecture 2 propositional calculus

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ARTIFICIAL INTELLIGENCE Lecture 2 Propositional Calculus

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Logic and Language Language is defined by: – Syntax: defines the sentences in the language – Semantics: define the "meaning" of sentences i.e. define truth of a sentence in the domain of discourse. Logic: is a formal language for representing information such that conclusions can be drawn.

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Page 1: ARTIFICIAL INTELLIGENCE Lecture 2 Propositional Calculus

ARTIFICIAL INTELLIGENCE

Lecture 2Propositional Calculus

Page 2: ARTIFICIAL INTELLIGENCE Lecture 2 Propositional Calculus

Contents

• Introduction • Propositional Logic• Propositional Calculus Syntax– Symbols-Sentences– Well Formed Formula

• Prepositional Calculus Semantics• Methods of Proof• Pros and Cons of Propositional Calculus

Page 3: ARTIFICIAL INTELLIGENCE Lecture 2 Propositional Calculus

Logic and Language

• Language is defined by:– Syntax: defines the sentences in the language– Semantics: define the "meaning" of sentences

i.e. define truth of a sentence in the domain of discourse.

• Logic: is a formal language for representing information such that conclusions can be drawn.

Page 4: ARTIFICIAL INTELLIGENCE Lecture 2 Propositional Calculus

PROPOSITIONAL CALCULUS SYNTAX SYMBOLS

• The symbols of propositional calculus are the • Propositional Symbols: P,Q, R,S,T,... • Truth Symbols: true, false • Connectives: , , , ,

– Propositional symbols denote propositions, or statements about the world that may be either true or false, such as

– “Car is red" – “Weather is bad."

• Propositions are denoted by uppercase letters near the end of the English alphabet.

• Sentences in the propositional calculus are formed from these atomic symbols according to the following rules:

Page 5: ARTIFICIAL INTELLIGENCE Lecture 2 Propositional Calculus

SENTENCES

• Every propositional symbol and truth symbol is a sentence. – For example: true, P, Q, and R are sentences.

• The negation of a sentence is a sentence. – For example: P and false are sentences.

• The conjunction (and), of two sentences is a sentence. – For example: P P is a sentence.

• The disjunction (or,) of two sentences is a sentence. – For example: P P is a sentence.

• The implication of one sentence for another is a sentence. – For example: P Q is a sentence.

• The equivalence of two sentences is a sentence. – For example: P Q = R is a sentence.

Page 6: ARTIFICIAL INTELLIGENCE Lecture 2 Propositional Calculus

SENTENCES

• A Legal sentence is also called well-formed formula or WFF.

• In expressions of the form P Q, P and Q are called the conjuncts.

• In P v Q, P and Q are referred to as disjuncts. • In an implication, P Q,

P is the premise or antecedent and Q, the conclusion or consequent.

Page 7: ARTIFICIAL INTELLIGENCE Lecture 2 Propositional Calculus

Well-Formed Sentence• Symbols ( ) and [ ] are used to group symbols into sub

expressions and so control their order of evaluation and meaning. For example, (P Q) = R is quite different from P (Q = R).

• An expression is a sentence, or well-formed formula, of the propositional calculus if and only if it can be formed of legal symbols through some sequence of these rules. For example, ((P Q) => R) = P Q R is a well-formed sentence in the propositional calculus. Why?

Page 8: ARTIFICIAL INTELLIGENCE Lecture 2 Propositional Calculus

ROPOSITIONAL CALCULUS SEMANTICS

• An interpretation is a mapping from the propositional symbols into the set {T, F}.

• Each possible mapping of truth value onto propositions corresponds to a possible world of interpretation.

• For example, if P denotes the proposition "it is raining" and Q denotes "I am at work," then the set of propositions {P, Q} has four different functional mappings into the truth values {T, F}. These mappings correspond to four different interpretations.

• An interpretation of a set of propositions is the assignment of a truth value, either T or F, to each propositional symbol.

• The symbol true is always assigned T, and the symbol false is assigned F.

Page 9: ARTIFICIAL INTELLIGENCE Lecture 2 Propositional Calculus

ROPOSITIONAL CALCULUS SEMANTICS• The interpretation or truth value for sentences is determined by:• The truth assignment of negation, P, where P is any propositional symbol, is F

if the assignment to P is T, and T if the assignment to P is F. • The truth assignment of conjunction, , is T only when both conjuncts have truth

value T; otherwise it is F. • The truth assignment of disjunction, , is F only when both disjuncts have truth

value F; otherwise it is T. • The truth assignment of implication, , is F only when the premise or symbol

before the implication is T and the truth value of the consequent or symbol after the implication is F; otherwise it is T.

• The truth assignment of equivalence, , is T only when both expressions have the same truth assignment for all possible interpretations; otherwise it is F.

Page 10: ARTIFICIAL INTELLIGENCE Lecture 2 Propositional Calculus

Equivalence Laws• Idempotency Law: P P= P , P P= P• Involution Law: (P) P• commutative law: (P Q) (Q P) and

(P Q) (Q P) • associative law: ((P Q) R) (P (Q R))

((P Q) R) (P (Q R)) • distributive law: P (Q R) (P Q) (P R)

P (Q R) = (P Q) (P R)

Page 11: ARTIFICIAL INTELLIGENCE Lecture 2 Propositional Calculus

Equivalence Laws

• de Morgan's law: (P v Q) ( P Q) (P Q) ( P Q)

• the contrapositive law: (P Q) ( Q P) • Conditional Elimination: (P Q) ( P Q)• Bidirectional Elimination • (P Q) (P Q) (Q P)

Page 12: ARTIFICIAL INTELLIGENCE Lecture 2 Propositional Calculus

Examples

• Prove the Conditional Elimination law:• (P Q) ( P Q)

P Q P P Q P Q P QT T F T T T

T F F F F T

F T T T T T

F F T T T T

Page 13: ARTIFICIAL INTELLIGENCE Lecture 2 Propositional Calculus

Methods of proof

• Truth table enumeration Check the truth value of statement for all interpretations

• Application of inference rulesDerive new sentences which are logical consequences of s1,s2,…,sn using only syntactic operations

Page 14: ARTIFICIAL INTELLIGENCE Lecture 2 Propositional Calculus

Pros and cons of propositional calculusRef[AIMA]

Propositional logic is declarative Propositional logic allows partial/disjunctive/negated

information– (unlike most data structures and databases)

Propositional logic is compositional:– meaning of B P is derived from meaning of B and of P

Meaning in propositional logic is context-independent– (unlike natural language, where meaning depends on

context) Propositional logic has very limited expressive power– (unlike natural language)– E.g., cannot say “There is free place in adjacent squares“• except by writing one sentence for each square