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1 Inference in First-Order Logic Proofs Unification Generalized modus ponens Forward and backward...

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1 Inference in First-Order Logic Proofs Unification Generalized modus ponens Forward and backward chaining Completeness Resolution Logic programming
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Page 1: 1 Inference in First-Order Logic Proofs Unification Generalized modus ponens Forward and backward chaining Completeness Resolution Logic programming.

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Inference in First-Order Logic

• Proofs

• Unification• Generalized modus ponens• Forward and backward chaining

• Completeness

• Resolution

• Logic programming

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Inference in First-Order Logic

• Proofs – extend propositional logic inference to deal with quantifiers

• Unification• Generalized modus ponens• Forward and backward chaining – inference rules and reasoning

program• Completeness – Gödel’s theorem: for FOL, any sentence

entailed byanother set of sentences can be proved from that set

• Resolution – inference procedure that is complete for any set ofsentences

• Logic programming

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Remember:propositionallogic

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Proofs

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Proofs

The three new inference rules for FOL (compared to propositional logic) are:

• Universal Elimination (UE):for any sentence , variable x and ground term ,

x {x/}

• Existential Elimination (EE):for any sentence , variable x and constant symbol k not in KB,

x {x/k}

• Existential Introduction (EI):for any sentence , variable x not in and ground term g in ,

x {g/x}

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Proofs

The three new inference rules for FOL (compared to propositional logic) are:

• Universal Elimination (UE):for any sentence , variable x and ground term ,

x e.g., from x Likes(x, Candy) and {x/Joe} {x/} we can infer Likes(Joe, Candy)

• Existential Elimination (EE):for any sentence , variable x and constant symbol k not in KB,

x e.g., from x Kill(x, Victim) we can infer{x/k} Kill(Murderer, Victim), if Murderer new

symbol

• Existential Introduction (EI):for any sentence , variable x not in and ground term g in ,

e.g., from Likes(Joe, Candy) we can inferx {g/x} x Likes(x, Candy)

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Example Proof

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Example Proof

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Example Proof

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Example Proof

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Search with primitive example rules

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Unification

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Unification

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Generalized Modus Ponens (GMP)

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Soundness of GMP

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Properties of GMP

• Why is GMP and efficient inference rule?

- It takes bigger steps, combining several small inferences into one

- It takes sensible steps: uses eliminations that are guaranteedto help (rather than random UEs)

- It uses a precompilation step which converts the KB to canonical

form (Horn sentences)

Remember: sentence in Horn from is a conjunction of Horn clauses(clauses with at most one positive literal), e.g.,(A B) (B C D), that is (B A) ((C D) B)

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Horn form

• We convert sentences to Horn form as they are entered into the KB

• Using Existential Elimination and And Elimination

• e.g., x Owns(Nono, x) Missile(x) becomes

Owns(Nono, M)Missile(M)

(with M a new symbol that was not already in the KB)

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Forward chaining

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Forward chaining example

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Backward chaining

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Backward chaining example

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Completeness in FOL

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Historical note

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Resolution

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Resolution inference rule

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Remember: normal forms

“sum of products of simple variables ornegated simple variables”

“product of sums of simple variables ornegated simple variables”

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Conjunctive normal form

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Skolemization

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Resolution proof

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Resolution proof


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