AR for Horn clause logicAR for Horn clause logic

Introducing: Introducing: UnificationUnification

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How to deal with variables? How to deal with variables? Example:Example:

p p lot_maint(house(p))lot_maint(house(p)) big(house(p)) big(house(p))false false lot_maint(house(Bos))lot_maint(house(Bos))

We would like to conclude:We would like to conclude:

by means of generalized modus ponens.by means of generalized modus ponens.

false false big(house(Bos)) big(house(Bos))

Principle:Principle: use instantiations of the 2 Horn use instantiations of the 2 Horn clauses, such that these DO ‘match’.clauses, such that these DO ‘match’.

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More examples:More examples: We drop the universal quantification, since all We drop the universal quantification, since all

variables are universally quantified anyway. variables are universally quantified anyway.

Some examples using standard modus ponens:Some examples using standard modus ponens:

related(related(xx,,yy) ) parent( parent(xx,,yy)) parent(John,Mary)parent(John,Mary)related(related(JohnJohn,,MaryMary))

loves(John,loves(John,xx) ) related(John, related(John,xx)) related(related(yy,father(,father(yy))))

loves(John,loves(John,father(John)father(John)))

Unification !!Unification !!

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Substitutions:Substitutions: Examples:Examples:

={={ x x // h(g(A))h(g(A)) , , y y // g(A)g(A) ,, z z // ww}}

= {= { x x // g(z)g(z) ,, y y // BB}}

A A substitutionsubstitution is a is a finite set of pairsfinite set of pairs of the form of the form variable variable // termterm, such that all , such that all variablesvariables at the at the left-hand sides of the pairs are distinct. left-hand sides of the pairs are distinct.

In our substitutions we will NOT allow that some In our substitutions we will NOT allow that some variablevariable that occurs left also occurs in some that occurs left also occurs in some termterm at the right. at the right.

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Applying substitutions:Applying substitutions:

Substitutions can be Substitutions can be appliedapplied to to simple simple expressionsexpressions (atoms or terms), by replacing all (atoms or terms), by replacing all occurrences of the left-side occurrences of the left-side variablesvariables in the in the expression by the corresponding expression by the corresponding termsterms..

= {= { x x // g(z)g(z) ,, y y // BB}}

p(p(xx , f(, f(yy, z)), z)) = p(= p(g(z)g(z) , f(, f(BB, ,

z))z)) ={={ x x // h(g(A))h(g(A)) , , y y // g(A)g(A) ,, z z // ww}}

p(p(xx, f(, f(yy, , zz)) )) == p(p(h(g(A))h(g(A)) , f(, f(g(A)g(A) ,, ww))))

Examples:Examples:

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Remember the motivation:Remember the motivation:

We want substitutions that make atoms equal. We want substitutions that make atoms equal.

lot_maint(house(lot_maint(house(pp)))) big(house(p)) big(house(p))false false lot_maint(house(lot_maint(house(BosBos))))

The two atoms in the clauses:The two atoms in the clauses:

must be made must be made equalequal..

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““Unifiers”Unifiers” Example:Example:

S = {related(John,S = {related(John,xx), related(), related(yy,, father( father(yy))}))}

= {= {y y // JohnJohn,, x x // father(John)father(John)}} is a unifier foris a unifier for SS

SS = = {related({related(JohnJohn,,father(John)father(John))})}

Given a Given a setset of simple expressions of simple expressions SS, we call a , we call a substitution substitution a a unifierunifier for for SS if: if:

S S is a singleton is a singleton

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One more refinement:One more refinement: For deduction step:For deduction step: related(related(xx,,yy) ) parent( parent(xx,,yy))

parent(John,z)parent(John,z)

we have:we have: S = {parent(S = {parent(xx,,yy), parent(John,z)}), parent(John,z)}

and there are several unifiers:and there are several unifiers:

= {= {x x // JohnJohn, , y y // zz}}

= {= {x x // JohnJohn, , y y // MaryMary, z / , z / MaryMary}}

etcetc..

Only the most general one, Only the most general one, ,, allows to derive the allows to derive the strongest conclusion:strongest conclusion:

related(related(JohnJohn,,zz))

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Relation between these?Relation between these? Example:Example: S = {parent(S = {parent(xx,,yy), parent(John,z)}), parent(John,z)}

= {= {x x // JohnJohn, , y y // zz}} S S = {parent(= {parent(JohnJohn,,zz)})}

= {= {x x // JohnJohn, , y y // MaryMary, z / , z / MaryMary}}

S S = {parent(= {parent(JohnJohn,,MaryMary)})}

There exists a There exists a third third substitution:substitution:

= {z /= {z / MaryMary}} withwith S S = ( = (S S ) )

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Most general unifier:Most general unifier:

Given a set of simple expressions Given a set of simple expressions SS, a , a most most general unifiergeneral unifier for for SS is a unifier for is a unifier for SS, such , such that for all other unifiers that for all other unifiers for for SS, there exists a , there exists a third substitution third substitution such that: such that:

SS = (S= (S ))

Key-idea: create minimal instantiation changes!Key-idea: create minimal instantiation changes! Notation: Notation: = = mgumgu((SS) , or ) , or = = mgumgu((AA, , BB) for S = {A,B} ) for S = {A,B}

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Generalized modus ponens for Generalized modus ponens for Horn clausesHorn clauses

A B1 B2 … Bi … BnBi’ C1 C2 … Cm

(A B1 B2 … C1 C2 … Cm … Bn)

Generalized modus ponens must be further Generalized modus ponens must be further extended as:extended as:

where where = = mgu(mgu( BiBi,, Bi’Bi’))

NoteNote: : BiBi and and Bi’Bi’ must have the same predicate. must have the same predicate. CorrectnessCorrectness: due to correctness for all ground instances of this derivation. : due to correctness for all ground instances of this derivation.

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Example: a few stepsExample: a few steps

ObserveObserve: we will always provide the variables : we will always provide the variables with with new namesnew names in order to avoid ‘accidental’ in order to avoid ‘accidental’ clashes of names. clashes of names.

false lot_maint(house(x)) lot_maint(house(y)) big(house(y))

false big(house(y))

false showm(z) belg(z) showm(Bos)

false belg(Bos)

Another step, much later:Another step, much later:

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Backward procedure Backward procedure for Horn clausesfor Horn clauses

Goal Goal := := false false B1 B1 B2 B2 … … Bn Bn ; ;RepeatRepeat

Select some Select some BiBi atom from the body of atom from the body of GoalGoal Select some clause Select some clause Bi’ Bi’ C1 C1 C2 C2 … … Cm Cm from from TT such that such that = mgu( = mgu(BiBi,, Bi’Bi’)) exists exists

GoalGoal := := false false (B1 (B1 … … Bi-1 Bi-1 C1 C1 C2 C2 … … Cm Cm Bi+1 Bi+1 … … Bn) Bn) UntilUntil GoalGoal = = false false or no more Selections possible or no more Selections possible

AgainAgain: concrete versions of this generic scheme : concrete versions of this generic scheme should allow for should allow for backtrackingbacktracking over previous selections, over previous selections,

or they should treat the problem as a or they should treat the problem as a general search general search problemproblem through the space of derivable goals. through the space of derivable goals.

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The example again:The example again:

false lot_maint(house(x))

european(x) belg(x)rich(x) showm(x) european(x)big(house(x)) rich(x)lot_maint(house(x)) big(house(x))false lot_maint(house(x))

showm(Bos)belg(Bos)

lot_maint(house(x1)) big(house(x1)) = { x1 / x}= { x1 / x}

false big(house(x)) = { x2 / x}= { x2 / x}

big(house(x2)) rich(x2)

false rich(x) = { x3 / x }= { x3 / x }rich(x3) showm(x3) european(x3)

false showm(x) european(x)

false showm(x) belg(x)

european(x4) belg(x4) = { x4 / x }= { x4 / x }

belg(Bos) = { x / Bos }= { x / Bos }

false showm(Bos) showm(Bos) = { }= { }

false

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Why rename variables?Why rename variables?

false p(x) p(y) q(z,y) false q(z,y) = {= {xx//yy } }

false p(x) p(y) q(x,y) false q(y,y) = {= {xx//yy }}

Consider the derivation step:Consider the derivation step:

Problem: Problem: p(y) p(y) q( q(xx,y),y) is equivalent with is equivalent with p(y) p(y) q(q(zz,y),y) so that alternatively we could perform the step: so that alternatively we could perform the step:

Which gives us a strictly stronger conclusion !Which gives us a strictly stronger conclusion !

Always first rename variables apart !!Always first rename variables apart !!

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Another example:Another example:anc(x,y) parent(x,y) (1)anc(x,y) parent(x,z) anc(z,y) (2)parent(A,B) (3) parent(B,C) (4)false anc(u,v)

false anc(u,v)

false parent(x1,z1) anc(z1,y1)

(2) {u/x1,v/y1}

false anc(B,y1)(3) {x1/A,z1/B}

false parent(B,y1)(1) {x2/B,y2/y1}

false (4) {y1/C}

false parent(x1,y1)(1) {u/x1,v/y1}

false (3) {x1/A,y1/B}

false

(4) {x1/B,y1/C}

Several different proofs are possible !Several different proofs are possible !

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Semi-deciding:Semi-deciding: Backward generalized modus ponens, Backward generalized modus ponens, using a using a

complete search method complete search method to search the space of to search the space of derived goals and derived goals and with renaming with renaming of variables of variables is is semi-decidingsemi-deciding..

Remark that it can Remark that it can only be semi-decidingonly be semi-deciding, , because the search space of goals may be because the search space of goals may be infinitely large. infinitely large.

thus, in general, this cannot help us to decide thus, in general, this cannot help us to decide whether whether false false is derivable. is derivable.

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An infinite derivation:An infinite derivation: ExampleExample:: nat(s(x)) nat(x)

false nat(u)

false nat(u)

false nat(x1)

{{uu//s(x1)s(x1)}}

false nat(x2)

{{x1x1//s(x2)s(x2)}}

...

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Using a complete searchUsing a complete searchwe do get an answer for:we do get an answer for:

ExampleExample:: nat(0)nat(s(x)) nat(x)false nat(u)

false nat(u)

false nat(x1)

{{uu//s(x1)s(x1)}}

false nat(x2)

{{x1x1//s(x2)s(x2)}}

...

false {{uu//00}}

false {{x1x1//00}}

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Deducing with unificationDeducing with unification Example:Example:

is impliedis implied: : mgumgu = {= {uu//point(1,z)point(1,z)}}

is impliedis implied: : mgumgu = {= {uu//yy,,vv//yy } }

vertical(segment(point(x,y),point(x,z)))vertical(segment(point(x,y),point(x,z)))horizontal(segment(point(x,y),point(z,yhorizontal(segment(point(x,y),point(z,y))))))

u vertical(segment(point(1,2),u))u vertical(segment(point(1,2),u))

u,v horizontal(segment(point(1,u),point(2,v)))u,v horizontal(segment(point(1,u),point(2,v)))

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Representation-powerRepresentation-powerof Horn clausesof Horn clauses

Most predicate logic formulae can easily be Most predicate logic formulae can easily be rewritten in Horn clauses.rewritten in Horn clauses.

Examples:Examples:

x cat(x) x cat(x) dog(x) dog(x) pet(x) pet(x)

x poodle(x) x poodle(x) dog(x) dog(x) small(x) small(x)

pet(x) cat(x)pet(x) dog(x)

dog(x) poodle(x)small(x) poodle(x)

BUTBUT::

x human(x) x human(x) male(x) male(x) female(x) female(x)

x dog(x) x dog(x) ~abnormal(x) ~abnormal(x) has_4_legs(x) has_4_legs(x)

????

????