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2.1 Sets 2.2 Set Operations – – – – Set Operations Venn Diagrams Set Identities Union and Intersection of Indexed Collections 2.3 Functions 2.4 Sequences and Summations 1 P. 1 Set Operations • Propositional calculus and set theory are both instances of an algebraic system called a Boolean Algebra. • The operators in set theory are defined in terms of the corresponding operator in propositional calculus. • As always there must be a universe U. All sets are assumed to be subsets of U. 2 P. 1 Set Operations • Definition: Two sets A and B are equal, denoted A = B, iff x[x A ↔ x B]. • Note: By a previous logical equivalence we have A = B iff x[(x A→ x B) Λ (x B → x A)] or A = B iff A B and B A 3 P. 1 Set Operations • Definitions: – The union of A and B, denoted AB, is the set {x | xA V xB} – The intersection of A and B, denoted AB, is the set {x | xA Λ xB} FIGURE 1 ∪ FIGURE 2 ∩ 4 P. 1 Set Operations • Note: If the intersection is void, A and B are said to be disjoint. – The complement of A, denoted A , is the set {x | x A}={x | ¬(xA)} • Note: Alternative notation is A C, and {x|xA}. – The difference of A and B, or the complement of B relative to A, denoted A - B, is the set A B • Note: The complement of A is U - A. – The symmetric difference of A and B, denoted AB, is the set (A - B)(B - A). 5 P. 1 Set Operations • Examples: U = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10} A= {1, 2, 3, 4, 5}, B = {4, 5, 6, 7, 8}. Then – – – – – – – AB = {1, 2, 3, 4, 5, 6, 7, 8} AB = {4, 5} A = {0, 6, 7, 8, 9, 10} B = {0, 1, 2, 3, 9, 10} A - B = {1, 2, 3} B - A = {6, 7, 8} A B = {1, 2, 3, 6, 7, 8} 6 P. 1 Venn Diagrams • A useful geometric visualization tool (for 3 or less sets) – The Universe U is the rectangular box. – Each set is represented by a circle and its interior. – All possible combinations of the sets must be represented. • Shade the appropriate region to represent the given set operation. 7 P. 1 Set Identities • Set identities correspond to the logical equivalences. • Example: The complement of the union is the intersection of the complements A B A B 8 P. 1 Set Identities • Proof: To show x[ x A B x A B] To show two sets are equal we show for all x that x is a member of one set if and only if it is a member of the other. • We now apply an important rule of inference (defined later) called Universal Instantiation 9 Set Identities • Universal Instantiation In a proof we can eliminate the universal quantifier which binds a variable if we do not assume anything about the variable other than it is an arbitrary member of the Universe. We can then treat the resulting predicate as a proposition. 10 Set Identities • We say 'Let x be arbitrary. ' Then we can treat the predicates as propositions: Assertion Reason Def. of complement x A B x [A B] Def. of x A B ¬[ x A B] ¬[ x A x B] Def. of union ¬ xA Λ ¬ x B DeMorgan's Laws Def. of x A xB Def. of complement x A xB Def. of intersection x A B Hence x A B x A B is a tautology. 11 P. 1 Set Identities Since – x was arbitrary – we have used only logically equivalent assertions and definitions we can apply another rule of inference called Universal Generalization We can apply a universal quantifier to bind a variable if we have shown the predicate to be true for all values of the variable in the Universe. and claim the assertion is true for all x, i.e., x[ x A B x A B ] P. 1 Set Identities • Q. E. D. (an abbreviation for the Latin phrase “Quod Erat Demonstrandum” - “which was to be demonstrated” used to signal the end of a proof) • Note: As an alternative which might be easier in some cases, use the identity A B [A B and B A] 13 Set Identities • Example: Show A(B - A) = Ø The void set is a subset of every set. Hence, A (B - A) Ø Therefore, it suffices to show A(B - A) Ø or x[x A (B - A) → x Ø] 14 P. 1 Set Identities So as before we say 'let x be arbitrary’. Show x A (B- A) → x Ø is a tautology. But the consequent is always false. Therefore, the antecedent better always be false also. 15 Set Identities • Solution: Apply the definitions: Assertion x A(B- A)x A Λ x (B- A) x A Λ (x B Λ x A) (x A Λ x A) Λ x B 0ΛxB 0 (false) Reason by Def. of by Def. of by Def. of Associative by Def. of Complement by Def. of Domination 16 P. 1 Union and Intersection of Indexed Collections • Let A1,A2 ,..., An be an indexed collection of sets. • Definition: The union of a collection of sets is the set that contains those elements that are members of at least one set in the collection. we use the notation n i 1 Ai A1 A2 ... An to denote the union of the sets A1,A2 ,..., An 17 P. 1 Union and Intersection of Indexed Collections • Definition: The intersection of a collection of sets is the set that contains those elements that are members of all the set in the collection. we use the notation n i 1 Ai A1 A2 ... An to denote the intersection of the sets A1,A2 ,..., An 18 Union and Intersection of Indexed Collections • Examples: • Let Ai [i, ),1 i n Ai [1, ) n Ai [n, ) i 1 i 1 19 P. 1 Terms • • • • • • Boolean Algebra Set operations Union Intersection Complement Difference • • • • • Symmetric difference Venn Diagram Set Identities Universal Instantiation Universal Generalization 20 P. 1