Lecture+14_Unification-1

# Lecture+14_Unification-1 - CS 401 Artificial Intelligence...

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CS 401 Artificial Intelligence Lecture # 14 Friday, March 10, 2017 Spring 2017 FAST NUCES, Faisalabad Campus Zain Iqbal [email protected] 1

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Topics Example of predicate Unification Composition of unification Function to unify Financial Advisor Example 2
Examples Emma is a Doberman pinscher and a good dog: Googdog(emma) ^ isa (emma,doberman). every dog is an animal: V X (dog(X) => animal (X)). every boy has a bicycle: V X (E Y (boy(X) => (bicycle(Y) ^ own(X,Y)))). 3

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Few More Examples…. 4
Unification Why? To apply inference rules such as modus ponens, an inference system must be able to determine when two expressions are the same or match In propositional calculu s, this is trivial: two expressions match if and only if they are syntactically identical In predicate calculus , the process of matching two sentences is complicated by the existence of variables in the expressions 5

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Unification Unification The process of finding the substitutions needed to make two predicate calculus expressions match. Example: {foo(X,a,goo(Y)), foo(fred, a, goo(Z))} - Substitution {fred/X} yields {foo(fred,a,goo(Y), foo(fred, a, goo(Z))} - substitution: {fred/X, Z/Y} yields {foo(fred,a,goo(Z), foo(fred, a, goo(Z))} - here ‘ fred /X’ indicates that ‘ fred ’ is substituted for the variable X or the variable X is said to be bound to the value ‘ fred Unification Rules a variable may be replaced by a constant: c/X a variable may be replaced by a variable: Y/X a variable may be replaced by a function expression as long as the function expression does not contain the variable: p(Y)/X once a variable has been bound, future unification and inferences must take this substitution into account 6
Restrictions

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