l3 - Knowledge Representation Lecture 3 More Logic Semantic...

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Knowledge Representation Lecture 3 More Logic Semantic Networks and Frames
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From lecture 2. . Need formal notation to represent knowledge, allowing automated inference and problem solving. One popular choice is use of logic. Propositional logic is the simplest. Symbols represent facts: P, Q, etc. . These are joined by logical connectives (and, or, implication) e.g., P Q; Q R Given some statements in the logic we can deduce new facts (e.g., from above deduce R)
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Predicate Logic Propositional logic isn’t powerful enough as a general knowledge representation language. Impossible to make general statements. E.g., “all students sit exams” or “if any student sits an exam they either pass or fail”. So we need predicate logic. .
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Predicate Logic In predicate logic the basic unit is a predicate/ argument structure called an atomic sentence: likes(alison, chocolate) tall(fred) Arguments can be any of: constant symbol, such as ‘alison’ variable symbol, such as X function expression, e.g., motherof(fred) So we can have: likes(X, richard) friends(motherof(joe), motherof(jim))
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Predicate logic: Syntax These atomic sentences can be combined using logic connectives likes(john, mary) L tall(mary) tall(john) L nice(john) Sentences can also be formed using quantifiers L (forall) and L (there exists) to indicate how to treat variables: L X lovely(X) Everything is lovely. L X lovely(X) Something is lovely. L X in(X, garden) Llovely(X) Everything in the garden is lovely.
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Predicate Logic Can have several quantifiers, e.g., L X L Y loves(X, Y) L X handsome(X) L L Y loves(Y, X) So we can represent things like: All men are mortal. No one likes brussel sprouts.
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This note was uploaded on 05/12/2010 for the course IT expirt taught by Professor Tt during the Spring '10 term at Dubai Aerospace Enterprise University.

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l3 - Knowledge Representation Lecture 3 More Logic Semantic...

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