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On the proof theory for Description Logics
1. On the Proof Theory for Description Logics
Alexandre Rademaker
March 30, 2010
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 1 / 58
2. Description Logics
Description Logics
Notations and Formalism for KR
FOL −→ Semantic-Network −→ Conceptual-Graphs −→ DLs
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 2 / 58
3. Description Logics
Description Logics
Decidable Fragments of FOL
Binary (Roles) and unary (Concepts) predicate symbols, R(x, y )
and C(y ).
Prenex Guarded formulas (∀y (R(x, y ) → C(y )),
∃y (R(x, y ) ∧ C(y ))).
Non-trivial extensions (transitive Closure R ∗ ).
Essentially propositional (Tboxes), but may involve reasoning on
individuals (Aboxes).
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 2 / 58
4. Description Logics
ALC is the core of DLs
Syntax:
φc ::= ⊥ | A | ¬φc | φc φc | φc φc | ∃R.φc | ∀R.φc
φf ::= φc φc | φc ≡ φc
Axiomatic Presentation: (1) from C propositional taut, ∀R.C; (2)
∀R.(A B) ≡ ∀R.A ∀R.B;
Interpreting ALC into K modal-logic.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 3 / 58
5. Description Logics
ALC semantics
Given by: I = (∆I , I )
I = ∆I
⊥I = ∅
(¬C)I = ∆I C I
(C D)I = C I ∩ DI
(C D)I = C I ∪ DI
(∃R.C)I = {a ∈ ∆I | ∃b.(a, b) ∈ R I ∧ b ∈ C I }
(∀R.C)I = {a ∈ ∆I | ∀b.(a, b) ∈ R I → b ∈ C I }
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 4 / 58
6. Description Logics
A T-Box on Family Relationships
Woman ≡ Person Female
Man ≡ Person ¬Woman
Mother ≡ Woman ∃hasChild.Person
Father ≡ Man ∃hasChild.Person
Parent ≡ Father Mother
Grandmother ≡ Mother ∃hasChild.Parent
MotherWithoutDaughter ≡ Mother ∀hasChild.¬Woman
MotherInTrouble ≡ Mother ≥ 10hasChild
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 5 / 58
7. Description Logics
Some definitions
Definition
The concept description D subsumes the concept description C,
written C D, if and only if C I ⊆ D I for all interpretations I.
Definition
C is satisfiable if and only if there exists an interpretation I such that
C I = ∅.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 6 / 58
8. Description Logics
Some definitions
Definition
C is valid or a tautology if and only if for all interpretation I, C I ≡ ∆I .
Definition
C and D are equivalent, written C ≡ D, if and only if C D and D C.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 6 / 58
9. The Sequent Calculus SCALC
An ALC Sequent Calculus: main motivation
DL have implemented reasoners and editors. However, they do
not have good, if any, support for explanations.
Simple Tableaux (without analytical cuts) cannot produce short
proofs (polynomially lengthy proofs). Sequent Calculus (SC) (with
the cut rule) has short proofs.
We have an industrial application problem with explanations
requirement.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 7 / 58
10. The Sequent Calculus SCALC
Labeled Formulas
LB → ∀R | ∃R
L → LB, L | ∅
φlc → L φc
Each labeled ALC concept has an straightforward ALC concept
equivalent. For example:
∃R2 .∀Q2 .∃R1 .∀Q1 .α ≡ ∃R2 ,∀Q2 ,∃R1 ,∀Q1 α
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 8 / 58
14. The Sequent Calculus SCALC
SCALC
Generalization rules
δ⇒ Γ ∆⇒ γ
+∃R
prom-∃ prom-∀
δ ⇒ +∃R Γ +∀R
∆⇒ +∀R γ
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 9 / 58
15. The Sequent Calculus SCALC
SCALC example
Doctor ⇒ Doctor
prom-∀
∀child
Doctor ⇒ ∀child Doctor
weak-l
, ∀child Doctor ⇒ ∀child Doctor
¬-r
⇒ ∃child ¬Doctor ,∀child Doctor
∃-r
⇒ ∃child.¬Doctor , ∀child Doctor
prom-∃
∃child
⇒ ∃child (∃child.¬Doctor ), ∃child,∀child Doctor
¬-l
∃child
, ∀child ¬(∃child.¬Doctor ) ⇒ ∃child,∀child Doctor
∀-l
∃child
, ∀child ¬(∃child.¬Doctor ) ⇒ ∃child ∀child.Doctor
∃-r
∃child
, ∀child ¬(∃child.¬Doctor ) ⇒ ∃child.∀child.Doctor
∃child
∀-l
, ∀child.¬(∃child.¬Doctor ) ⇒ ∃child.∀child.Doctor
∃-l
∃child. , ∀child.¬(∃child.¬Doctor ) ⇒ ∃child.∀child.Doctor
-l
∃child. ∀child.¬(∃child.¬Doctor ) ⇒ ∃child.∀child.Doctor
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 10 / 58
16. The Sequent Calculus SCALC
SCALC soundness
Theorem (SCALC is sound)
Considering Ω a set of sequents, a theory or a TBox, let an Ω-proof be
any SCALC proof in which sequents from Ω are permitted as initial
sequents (in addition to the logical axioms). The soundness of SCALC
states that if a sequent ∆ ⇒ Γ has an Ω-proof, then ∆ ⇒ Γ is satisfied
by every interpretation which satisfies Ω. That is,
if Ω SALC ∆ ⇒ Γ then Ω |= T (δ) T (γ)
δ∈∆ γ∈Γ
for all interpretation I.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 11 / 58
17. The Sequent Calculus SCALC
SCALC completeness
ALC sequent calculus deduction rules without labels behave
exactly as sequent calculus rules for classical propositional logic.
The derivation of the rule of necessitation
⇒α prom-∀
⇒ ∀R α ∀-r
⇒ ∀R.α
The axiom
∀R.(α β) ≡ ∀R.α ∀R.β
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 12 / 58
18. The Sequent Calculus SCALC
SCALC Cut elimination
We follow Gentzen’s original proof for cut elimination. Let δ be a
labeled formula. An inference of the following form is called mix with
respect to δ:
∆1 ⇒ Γ1 ∆2 ⇒ Γ2
(δ)
∆1 , ∆∗ ⇒ Γ∗ , Γ2
2 1
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 13 / 58
20. The Sequent Calculus SCALC
SCALC Cut elimination
∗
Definition (The SCALC system)
∗
We call SCALC the new system obtained from SCALC by replacing the
cut rule by the quasi-mix rules.
Lemma
∗
The systems SCALC and SCALC are equivalent, that is, a sequent is
∗
SCALC -provable if and only if that sequent is also SCALC -provable.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 13 / 58
21. The Sequent Calculus SCALC
SCALC Cut elimination
T
Definition (SCALC system)
SCALC was defined with initial sequents of the form α ⇒ α with α a
ALC concept definition (logical axiom). However, it is often convenient
to allow for other initial sequents. So if T is a set of sequents of the
form ∆ ⇒ Γ, where ∆ and Γ are sequences of ALC concept
T
descriptions (non-logical axioms), we define SCALC to be the proof
system defined like SCALC but allowing initial sequents to be from T
too.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 13 / 58
22. The Sequent Calculus SCALC
SCALC Cut elimination
Definition (Free-quasi-mix free proof)
∗T
Let P be an SCALC -proof. A formula occurring in P is anchored (by an
T -sequent) if it is a direct descendent of a formula occurring in an
initial sequent in T . A quasi-mix inference in P is anchored if either: (i)
the mix formulas are not atomic and at least one of the occurrences of
the mix formulas in the upper sequents is anchored, or (ii) the mix
formulas are atomic and both of the occurrences of the mix formulas in
the upper sequents are anchored. A quasi-mix inference which is not
anchored is said to be free. A proof P is free-quasi-mix free if it
contains no free quasi-mixes.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 13 / 58
23. The Sequent Calculus SCALC
SCALC Cut elimination
Theorem (Free-mix Elimination)
∗T
Let T be a set of sequents. If SCALC ∆ ⇒ Γ then there is a
∗T
free-quasi-mix free SCALC -proof of ∆ ⇒ Γ.
Lemma
∗T
If P is a proof of S (in SCALC ) which contains only one free-quasi-mix,
occurring as the last inference, then S is provable without any free-mix.
The Theorem is obtained from the Lemma by simple induction over the
number of quasi-free-mix occurring in a proof P.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 13 / 58
24. The Sequent Calculus SCALC
SCALC Cut elimination
We prove the last lemma by lexicographically induction on the ordered
triple (grade,ldegree,rank ) of the proof P. We divide the proof into two
main cases, namely rank = 2 and rank > 2 (regardless of grade and
ldegree).
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 13 / 58
25. Comparing SCALC with other deduction systems
The Structural Subsumption algorithm
SSA deals with normalized concepts in FL0 ( , ∀R.C), and can
be extended to ALN (⊥, ¬A, ≤ R, ≥ R).
any concept description in FL0 can be transformed into an
equivalent in normal form.
Given C and D, C D iff the following two conditions holds:
C ≡ A1 ... Am ∀R1 .C1 ... ∀Rn .Cn
D ≡ B1 ... Bk ∀S1 .D1 ... ∀Sl .Dl
for 1 ≤ i ≤ k , ∃j, 1 ≤ j ≤ m such that Bi = Aj
for 1 ≤ i ≤ l, ∃j, 1 ≤ j ≤ n such that Si = Rj and Cj Di
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 14 / 58
26. Comparing SCALC with other deduction systems
The Tableaux algorithm
Strongly based on the use of individuals and FOL Tableaux.
C D iff C0 ≡ C ¬D is unsatisfiable. C0 in negation normal
form.
I
Try to construct a finite interpretation I such that C0 = ∅.
The individuals must satisfy the constraints (C0 clauses).
(+) It provides counter-model
(−) super-polynomial lengthy proofs
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 15 / 58
27. Comparing SCALC with other deduction systems
Comparing with SSA
Each step taken by a bottom-up construction of a SCALC proof
corresponds to a step towards this matching by means of the SSA.
⇒ S1 D1 R1 C
1
A1 ⇒ B1 ⇒ ∀S1 .D1R1 C
1
∀R1 .C1 , A1 ⇒ B1 ∀R1 .C1 ⇒ ∀S1 .D1
A1 , ∀R1 .C1 ⇒ B1 A1 , ∀R1 .C1 ⇒ ∀S1 .D1
A1 , ∀R1 .C1 ⇒ B1 ∀S1 .D1
A1 ∀R1 .C1 ⇒ B1 ∀S1 .D1
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 16 / 58
28. Comparing SCALC with other deduction systems
Refining SCALC towards Automatic Theorem Proving
[]
SCALC was extended to SALC in order to be able to construct a
counter-model from unsuccessful proofs;
Determinism to avoid backtracking in proof search;
Alternative cut-elimination and completeness (for SCALCQI );
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 17 / 58
29. Comparing SCALC with other deduction systems
Refining SCALC towards Automatic Theorem Proving
Example
An unsuccessful proof of a valid sequent in SCALC :
⇒ ∀child Doctor
prom-∃
∃child
⇒ ∃child,∀child Doctor
weak-l
∃child
, ∀child ¬(∃child.¬Doctor ) ⇒ ∃child,∀child Doctor
∀-r
∃child
child, ∀child ¬(∃child.¬Doctor ) ⇒ ∃child ∀child.Doctor
∃-r
∃child
, ∀child ¬(∃child.¬Doctor ) ⇒ ∃child.∀child.Doctor
∃child
∀-l
, ∀child.¬(∃child.¬Doctor ) ⇒ ∃child.∀child.Doctor
∃-l
∃child. , ∀child.¬(∃child.¬Doctor ) ⇒ ∃child.∀child.Doctor
-l
∃child. ∀child.¬(∃child.¬Doctor ) ⇒ ∃child.∀child.Doctor
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 17 / 58
30. Comparing SCALC with other deduction systems
Refining SCALC towards Automatic Theorem Proving
Example
A counter-model I not only has to guarantee B I AI but also
AI B I .
B⇒ A B⇒ B A⇒ A A⇒ B
-r -r
B⇒ A B A⇒ A B
prom-∃ prom-∃
∃R
B ⇒ ∃R A B ∃R
A ⇒ ∃R A B
∃R
weak-l weak-l
A, B ⇒ ∃R A B
∃R ∃R
A, B ⇒ ∃R A B
∃R
∃R
∃-r ∃-r
A, ∃R B ⇒ ∃R.A B ∃R
A, ∃R B ⇒ ∃R.A B
∃R
∃-l ∃R
∃-l
A, ∃R.B ⇒ ∃R.A B A, ∃R.B ⇒ ∃R.A B
∃-l ∃-l
∃R.A, ∃R.B ⇒ ∃R.A B ∃R.A, ∃R.B ⇒ ∃R.A B
-l -l
∃R.A ∃R.B ⇒ ∃R.A B ∃R.A ∃R.B ⇒ ∃R.A B
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 17 / 58
31. Comparing SCALC with other deduction systems
Refining SCALC towards Automatic Theorem Proving
[]
SALC sequents are expressions of the form ∆ ⇒ Γ that range over
labeled concepts and indexed-frozen labeled concept ([α]n , [∆]n ).
In frozen-exchange all formulas in ∆2 and Γ2 must be atomic;
Reading bottom-up, weak rules freeze all formulas saving the
context.
∆1 , [∆2 ]1 , . . . , [∆n ]n−1 ⇒ Γ1 , [Γ2 ]1 , . . . , [Γn ]n−1
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 17 / 58
32. Comparing SCALC with other deduction systems
Refining SCALC towards Automatic Theorem Proving
∆, δ ⇒ δ, Γ
[∆, δ]k , ∆ ⇒ Γ, [Γ]k [∆]k , ∆ ⇒ Γ, [Γ, γ]k
weak-l weak-r
∆, δ ⇒ Γ ∆ ⇒ Γ, γ
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 17 / 58
33. Comparing SCALC with other deduction systems
Refining SCALC towards Automatic Theorem Proving
∆, ∀L α, ∀L β ⇒ Γ ∆ ⇒ Γ, ∀L α ∆ ⇒ Γ, ∀L β
-l -r
∆, ∀L (α β) ⇒ Γ ∆ ⇒ Γ, ∀L (α β)
∆, ∃L α ⇒ Γ ∆, ∃L β ⇒ Γ ∆ ⇒ Γ, ∃L α, ∃L β
-l -r
∆, L (α β) ⇒ Γ ∆ ⇒ Γ, ∃L (α β)
∆ ⇒ Γ, ¬L α ∆, ¬L α ⇒ Γ
¬-l ¬-r
∆, L ¬α ⇒ Γ ∆ ⇒ Γ, L ¬α
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 17 / 58
34. Comparing SCALC with other deduction systems
Refining SCALC towards Automatic Theorem Proving
[∆], L δ ⇒ Γ, [Γ1 ] [∆1 ], ∆ ⇒ L γ, [Γ]
prom-∃ prom-∀
[∆], ∃R,L δ ⇒ +∃R
Γ, [Γ1 ] [∆1 ], +∀R ∆ ⇒ ∀R,L γ, [Γ]
[∆], [∆2 ]k , ∆1 ⇒ Γ1 , [Γ2 ]k , [Γ]
frozen-exchange
[∆], ∆2 , [∆1 ]n ⇒ [Γ1 ]n , Γ2 , [Γ]
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 17 / 58
35. Comparing SCALC with other deduction systems
Satisfability of frozen labeled sequents
Let ∆ ⇒ Γ be a sequent with its succedent and antecedent having
formulas that range over labeled concepts and frozen labeled concept.
This sequent has the general form of
∆1 , [∆2 ]1 , . . . , [∆n ]n−1 ⇒ Γ1 , [Γ2 ]1 , . . . , [Γn ]n−1
Let (I1 , . . . , In ) be a tuple of interpretations. We say that this tuple
satisfy ∆ ⇒ Γ, if and only if, one of the following clauses holds:
I1 |= ∆1 ⇒ Γ1 I2 |= ∆2 ⇒ Γ2 ... In |= ∆n ⇒ Γn
The sequent ∆ ⇒ Γ is not satisfiable by a tuple of interpretations, if and
only if, no interpretation in the tuple satisfy its corresponding context.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 18 / 58
36. Comparing SCALC with other deduction systems
[]
SALC properties
Lemma
[]
Consider ∆ ⇒ Γ a SCALC sequent. If P is a proof of ∆ ⇒ Γ in SCALC
then it is possible to construct a proof P of ∆ ⇒ Γ in SCALC .
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 19 / 58
37. Comparing SCALC with other deduction systems
[]
SALC properties
A fully expanded proof-tree of ∆ ⇒ Γ is a tree having ∆ ⇒ Γ as root,
[]
each internal node is a premise of a valid SCALC rule application, and
[]
each leaf is either a SCALC axiom (initial sequent) or a top-sequent
which is not an axiom, not necessarily atomic. In other words, a
sequent is a top-sequent if and only if it does not contain reducible
contexts.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 19 / 58
38. Comparing SCALC with other deduction systems
[]
SALC properties
If we consider a particular strategy of rules application any
full-expanded proof tree will have a special form called normal form.
1 only fair strategies of rules applications that avoid infinite loops;
2 Promotional rules will be applied whenever possible;
3 The strategy will discard contexts created by successive
applications of weak rules and avoid further applications of weak
rules once it is possible to detected that they will not be useful to
obtain an initial sequent;
4 Weak rules will be used with the unique purpose of enabling
promotion rules applications.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 19 / 58
40. Comparing SCALC with other deduction systems
∗[]
SCALC normal proof
[A]2 , [. . .]3 , B ⇒ A, [. . .]3 , [B]2 [A]2 , [. . .]3 , B ⇒ B, [. . .]3 , [B]2
-r
[A]2 , [∃R A, ∃R B]3 , B ⇒ A B, [∃R (A B)]3 , [B]2
prom-∃
[A]2 , [∃R A, ∃R B]3 , ∃R B ⇒ ∃R (A B), [∃R (A B)]3 , [B]2
weak ∗
[A]2 , ∃R A, ∃R B ⇒ ∃R (A B), [B]2
f-exch
[∃R A, ∃R B]1 , A ⇒ B, [∃R (A B)]1 [. . .]1 , A ⇒ A, [. . .]1
-r
[. . .]1 , A ⇒ A B, [. . .]1
prom-∃
[∃R A, ∃R B]1 , ∃R A ⇒ ∃R (A B), [∃R (A B)]1
∃R
weak ∗
A, ∃R B ⇒ ∃R (A B)
∃R
∃-r
A, ∃R B ⇒ ∃R.(A B)
∃R
∃-l
A, ∃R.B ⇒ ∃R.(A B)
∃R.A, ∃R.B ⇒ ∃R.(A B)
∃-l
∃R.A ∃R.B ⇒ ∃R.(A B)
-l
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 21 / 58
41. Comparing SCALC with other deduction systems
∗[]
SCALC normal proof
Π1 ≡
Π2
∃R
A, ∃R
B ⇒ ∃R (A B)
∃-r
∃R
A, ∃R B ⇒ ∃R.(A B)
∃-l
∃R
A, ∃R.B ⇒ ∃R.(A B)
∃-l
∃R.A, ∃R.B ⇒ ∃R.(A B)
-l
∃R.A ∃R.B ⇒ ∃R.(A B)
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 21 / 58
42. Comparing SCALC with other deduction systems
∗[]
SCALC normal proof
Π2 ≡
Π3
[. . .]1 , A ⇒ B, [. . .]1 [. . .]1 , A ⇒ A, [. . .]1
-r
[. . .]1 , A ⇒ A B, [. . .]1
prom-∃
[∃R A, ∃R B]1 , ∃R A ⇒ ∃R (A B), [∃R (A B)]1
Π3 ≡
[A]2 , [. . .]3 , B ⇒ A, [. . .]3 , [B]2 [A]2 , [. . .]3 , B ⇒ B, [. . .]3 , [B]2
-r
[A]2 , [. . .]3 , B ⇒ A B, [. . .]3 , [B]2
prom-∃
[A]2 , [∃R A, ∃R B]3 , ∃R B ⇒ ∃R (A B), [∃R (A B)]3 , [B]2
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 21 / 58
43. Comparing SCALC with other deduction systems
∗[]
SCALC : obtaining counter-models
Theorem
[]
If P is a full-expanded proof-tree in SCALC with sequent S as root
(conclusion) and if P is in the normal form, from any top-sequent not
initial (non-axiom), one can construct a counter-model for S.
To be fixed!
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 22 / 58
44. Comparing SCALC with other deduction systems
∗[]
SCALC : obtaining counter-models
Lemma
∗[]
If P is a full-expanded proof-tree in SCALC with sequent S as root
(conclusion) and if P is in the normal form, from any S1 top-sequent
not initial (non-axiom), we can construct a counter-model of S1 .
Lemma
If P is a weak ∗ -free proof fragment with at least one top-sequent not
initial and having S as the bottom sequent. That is, a fragment where
no weak rule were applied. If I is a counter-model for one of its
top-sequents, There is I that is a counter-model for S.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 22 / 58
45. Comparing SCALC with other deduction systems
∗[]
SCALC : obtaining counter-models
Lemma
Given a weak ∗ application with a conclusion S, reading top-down, this
application has two proof fragments with roots S1 and S2 , their
premise and the context that was frozen. If there are interpretations I1
and I2 such that I1 |= S1 and I2 |= S2 then there is I such that I |= S.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 22 / 58
46. A Natural Deduction for ALC
Motivation I
Natural Deduction (ND) proofs in intuitionistic logic (IL) have
computational content: Curry-Howard isomorphism.
Computational content of a proof should provide good structures
to explanation extraction from proofs.
An algorithm is one of the most precise arguments to explain how
to obtain a result out of some inputs.
ND is single-conclusion and provides, in this way, a direct chain of
inferences linking the propositions in the proof.
There is more than one ND normal proof related to the same
cut-free SC proof.
We believe that explanations should be as specific as their
proof-theoretical counterparts.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 23 / 58
47. A Natural Deduction for ALC
The NDALC system
L∀ L∀ L∀ α L∀
(α β) (α β) β
-e -e L∀
-i
L∀ L∀
α β (α β)
∃ ∃
[L α] [L β]
.
. .
.
.
. .
. L∃ α L∃
β
L∃
(α β) γ γ -i -i
-e L∃ L∃
γ (α β) (α β)
Lα
∀R,L α Gen
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 24 / 58
48. A Natural Deduction for ALC
The NDALC system
[L α] [¬L ¬α]
.
. .
.
.
. .
.
Lα ¬L ¬α ⊥ ⊥ ⊥
⊥
¬-e ¬L ¬α ¬-i Lα c
L L,∃R α L
∃R.α ∀R.α
L,∃R α ∃-e L ∃-i L,∀R α ∀-e
∃R.α
[L1 α]
.
.
.
.
L,∀R α L1 α L1 α L2 L2
β β
L ∀-i L2
-e L1 α L2
-i
∀R.α β β
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 24 / 58
49. A Natural Deduction for ALC
NDALC semantics
If Φ1 , Φ2 Ψ is an inference rule involving only concept formulas
then it states that whenever the premises are taken as non-empty
collections of individuals the conclusion is taken as non-empty too.
If a is an individual belonging to both interpreted concepts then it
also belongs to the interpreted conclusion.
A subsumption Φ Ψ has no concept associate to it. It states,
instead, a truth-value statement.
In terms of a logical system, DL has no concept internalizing .
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 25 / 58
50. A Natural Deduction for ALC
NDALC semantics
Definition
Let Ω = (C, S) be a tuple composed by a set of labeled concepts
C = {α1 , . . . , αn } and a set of subsumption
S = {γ1 γ2 , . . . , γ1 γ2 }. We say that an interpretation I = (∆I , I )
1 1 k k
satisfies Ω and write I |= Ω whenever:
1 I |= C, which means α∈C T I (α) = ∅; and
2 i
I |= S, which means that for all γ1 i
γ2 ∈ S, we have
T I (γ1 ) ⊆ T I (γ2 ).
i i
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 25 / 58
51. A Natural Deduction for ALC
NDALC soundness
Theorem
NDALC is sound regarding the standard semantics of ALC.
if Ω NDALC γ then Ω |= γ
Lemma
Let Π be a deduction in NDALC of F with all hypothesis in Ω = (C, S),
then:
If F is a concept: S |= A∈C A F and
If F is a subsumption A1 A2 : S |= A∈C A A1 A2
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 26 / 58
52. A Natural Deduction for ALC
NDALC completeness
NDALC is a conservative extension of the classical propositional
calculus.
NDALC has the generalization as a derived rule, and, proves
axiom ∀R.(A B) ≡ (∀R.A ∀R.B), we have the completeness for
NDALC by a relative completeness to the axiomatic presentation of
ALC.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 27 / 58
53. A Natural Deduction for ALC
NDALC normalization
Proposition
−
The NDALC -rules and ∃-rules are derived in NDALC .
Lemma (Moving ⊥c downwards on branches)
−
If Ω ND − α, then there is a deduction in NDALC of α from Ω where
ALC
each branch in Π has at most one application of ⊥c -rule and,
whenever it has one, it is the last rule applied in the branch.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 28 / 58
54. A Natural Deduction for ALC
NDALC normalization
Lemma (Eliminating maximal -formulas)
−
If Ω ND − α is a deduction in NDALC which contains maximal
ALC
-formulas, that is, maximal formulas with as principal sign, then
−
there is a deduction in NDALC of α from Ω without any occurrence of
maximal -formulas.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 28 / 58
55. A Natural Deduction for ALC
NDALC normalization
Theorem (normalization of NDALC )
−
If Ω −
NDALC α, then there is a normal deduction in NDALC of α from Ω.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 28 / 58
56. Towards to a proof theory for ALCQI
Introduction
Some pratical applications require a more expressive DL. For
instance, if we want to formalize and reasoning over ER or UML
diagrams using DL.
A sequent calculus and a natural deduction for ALCQI are
proposed.
Language ALCQI:
C ::= ⊥ | A | ¬C | C1 C2 | C1 C2 | ∃R.C | ∀R.C |
≤ nR.C | ≥ nR.C
R ::= P | P −
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 29 / 58
57. Towards to a proof theory for ALCQI
ALCQI semantics
(P − )I = {(a, a ) ∈ ∆I × ∆I | (a , a) ∈ P I }
(≤ nR)I = {a ∈ ∆I | |{b | (a, b) ∈ R I }| ≤ n}
(≥ nR)I = {a ∈ ∆I | |{b | (a, b) ∈ R I }| ≥ n}
(≤ nR.C)I = {a ∈ ∆I | |{b | (a, b) ∈ R I ∧ b ∈ C I }| ≤ n}
(≥ nR.C)I = {a ∈ ∆I | |{b | (a, b) ∈ R I ∧ b ∈ C I }| ≥ n}
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 30 / 58
58. Towards to a proof theory for ALCQI
The system SCALCQI
LB ::= ∀R | ∃R |≤ nR |≥ nR
R ::= P | P −
L ::= LB, L | ∅
φlc ::= L φc
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 31 / 58
59. Towards to a proof theory for ALCQI
The system SCALCQI
∆, L,≤nR α ⇒ Γ ∆ ⇒ Γ, L,≤nR α
≤-l ≤-r
∆, L ≤ nR.α ⇒ Γ ∆ ⇒ Γ, L ≤ nR.α
∆, L,≥nR α ⇒ Γ ∆ ⇒ Γ, L,≥nR α
≥-l ≥-r
∆, L ≥ nR.α ⇒ Γ ∆ ⇒ Γ, L ≥ nR.α
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 31 / 58
60. Towards to a proof theory for ALCQI
The system SCALCQI
∀≥ ∀≥ ∀≤ ∀≤
∆, L α, L β⇒ Γ ∆ ⇒ Γ, L α ∆ ⇒ Γ, L β
∀≥
-l ∀≤
-r
L L
∆, (α β) ⇒ Γ ∆ ⇒ Γ, (α β)
∃≤ ∃≤ ∃≥ ∃≥
∆, L α⇒ Γ ∆, L β⇒ Γ ∆ ⇒ Γ, L α, L β
-l -r
L∃≤ L∃≥
∆, (α β) ⇒ Γ ∆ ⇒ Γ, (α β)
∀∃ ∀∃
∆ ⇒ Γ, ¬L α ∆, ¬L α⇒ Γ
∀∃
¬-l ∀∃
¬-r
∆, L ¬α ⇒ Γ ∆ ⇒ Γ, L ¬α
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 31 / 58
61. Towards to a proof theory for ALCQI
The system SCALCQI
∆, ≥nR,L α ⇒ Γ ∆⇒ ≥nR,L α, Γ
n≤m shift-≥-l n≥m shift-≥-r
∆, ≥mR,L α ⇒ Γ ∆⇒ ≥mR,L α, Γ
∆, ≤nR,L α ⇒ Γ ∆⇒ ≤nR,L α, Γ
n≥m shift-≤-l n≤m shift-≤-r
∆, ≤mR,L α ⇒ Γ ∆⇒ ≤mR,L α, Γ
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 31 / 58
62. Towards to a proof theory for ALCQI
The system SCALCQI
∆, ≥1R,L α ⇒ Γ ∆ ⇒ Γ, ≥nR,L α
≥ ∃-l n≥1 ≥ ∃-r
∆, ∃R,L α ⇒ Γ ∆ ⇒ Γ, ∃R,L α
∆, ∃R,L α ⇒ Γ ∆ ⇒ Γ, ∃R,L α
n≥1 ∃ ≥-l ∃ ≥-r
∆, ≥nR,L α ⇒ Γ ∆ ⇒ Γ, ≥1R,L α
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 31 / 58
63. Towards to a proof theory for ALCQI
The system SCALCQI
∆, ∃R,L1 α ⇒ L2
β, Γ ∀R − ,L2
∆, L1 α ⇒ β, Γ
−
∃-inv inv-∃
∀R L2
∆, L1 α ⇒ ,L2
β, Γ ∆, ∃R,L1 α ⇒ β, Γ
∆⇒ Γ δ⇒ γ
prom-≥ prom-≤
+≥nR
∆ ⇒ +≥nR Γ +≤nR γ ⇒ +≤nR
δ
δ⇒ Γ ∆⇒ γ
prom-∃ prom-∀
+∃R
δ ⇒ +∃R Γ +∀R
∆⇒ +∀R γ
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 31 / 58
64. Towards to a proof theory for ALCQI
Example
In the proof below, Fem is an abbreviation for Female and child for
hasChild.
Fem ⇒ Fem Male ⇒ Male
∃child
Fem ⇒ ∃child Fem ∃child
Male ⇒ ∃child Male
≥1child
Fem ⇒ ∃child Fem ≥1child
Male ⇒ ∃child Male
≥1child
Fem ⇒ ∃child Male, ∃child Fem ≥1child
Male ⇒ ∃child Male, ∃child Fem
≥1child
Fem ⇒ ∃child (Male Fem) ≥1child
Male ⇒ ∃child (Male Fem)
≥1child ≥1child
Fem ⇒ ∃child.(Male Fem) Male ⇒ ∃child.(Male Fem)
≥ 1child.Fem ⇒ ∃child.(Male Fem) ≥ 1child.Male ⇒ ∃child.(Male Fem)
≥ 1child.Male ≥ 1child.Fem ⇒ ∃child.(Male Fem)
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 32 / 58
65. Towards to a proof theory for ALCQI
SCALCQI soundness
Theorem (SALCQ is sound)
Considering Ω a set of sequents, a theory presentation or a TBox, let
an Ω-proof be any SALCQ proof in which sequents from Ω are
permitted as initial sequents (in addition to the logical axioms). The
soundness of SALCQ states that if a sequent ∆ ⇒ Γ has an Ω-proof,
then ∆ ⇒ Γ is satisfied by every interpretation which satisfies Ω. That
is,
if Ω SCALCQI ∆⇒Γ then Ω |= T (δ) T (γ)
δ∈∆ γ∈Γ
for all interpretation I.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 33 / 58
66. Towards to a proof theory for ALCQI
SCALCQI soundness
Diagram 1 Diagram 2
≤ nR.(A B) / ≤ nR.A ≥ nR.(A B) o ≥ nR.A
SSS O iSSS
SSS SSS
SSS SSS
SSS SSS
SS) SS
≤ nR.B / (≤ nR.A) (≤ nR.B) ≥ nR.B / (≥ nR.A) (≥ nR.B)
Diagram 3 Diagram 4
≤ nR.(A B) o ≤ nR.A
O ≥ nR.(A B) / ≥ nR.A
O
O iSSS SSS
SSS SSS
SSS SSS
SSS SSS
SS SS)
≤ nR.B o (≤ nR.A) (≤ nR.B) ≥ nR.B o (≥ nR.A) (≥ nR.B)
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 33 / 58
67. Towards to a proof theory for ALCQI
SCALCQI completeness
The proof of SCALCQI completeness should be obtained following the
same strategy used for SCALC . A deterministic version of SCALCQI
[]
can be designed along the same basic idea used on SCALC .
Afterwards, provision of counter-example from fully expanded trees
that are not proofs must be obtained.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 34 / 58
68. Towards to a proof theory for ALCQI
The ND system NDALCQI
L∀≥ L∀≥ L∀≤ α L∀≤
(α β) (α β) β
-e -e L∀≤
-i
L∀≥ L∀≥
α β (α β)
∃≤ ∃≤
[L α] [L β]
.
. .
.
.
. .
. L∃≥ α L∃≥
β
L∃≤
(α β) γ γ -i -i
-e L∃≥ L∃≥
γ (α β) (α β)
∀∃ ∀∃
[L α] [¬L ¬α]
.
. .
.
.
. .
.
L∀∃ α ¬L∀∃ ¬α ⊥ ⊥ ⊥
¬-e ¬L∀∃ ¬α
¬-i L∀∃ α
c
⊥
L L,∃R α L
∃R.α ∀R.α
L,∃R α ∃-e L ∃-i L,∀R α ∀-e
∃R.α
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 35 / 58
69. Towards to a proof theory for ALCQI
The ND system NDALCQI
∃R,L α ≥nR,L α
≥1R,L α
≥∃ ∃R,L α
∃ ≥ (n ≥ 1)
≥mR,L α ≤mR,L α Lα
≥nR,L α
− ≥ (m ≥ n) ≤nR,L α
+ ≥ (m ≤ n) ∀R,L α Gen
[L1 α]
.
.
.
.
L1 α L1 α L2 L2 ∃R,L1 α L2
β β β
L2
-e L1 α L2
-i L1 α ∀R − ,L2
inv
β β β
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 35 / 58
70. Proof Explanation
Conceptual Modelling from a Logical Point of View
1 Observe the “World”.
2 Determine what is relevant.
3 Choose/Define your terminology (non-logical linguistic terms).
4 Write down the main laws governing your “World” (Axioms).
5 Verify the correctness (sometimes completeness too) of your set of Laws.
Steps 1 and 2 may be facilitated by the use of an informal notation (UML, ER, FlowCharts,
etc) and their respective methodology, but it is essentially “Black Art” (cf. Maibaum).
Step 5 full-filling demands quite a lot of knowledge of the Model.
Step 5 essentially provides finitely many tests as support for the correctness of an infinite
quantification.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 36 / 58
71. Proof Explanation
Conceptual Modelling from a Logical Point of View
1 Observe the “World”.
2 Determine what is relevant.
3 Choose/Define your terminology (non-logical linguistic terms).
4 Write down the main laws governing your “World” (Axioms).
5 Verify the correctness (sometimes completeness too) of your set of Laws.
Steps 1 and 2 may be facilitated by the use of an informal notation (UML, ER, FlowCharts,
etc) and their respective methodology, but it is essentially “Black Art” (cf. Maibaum).
Step 5 full-filling demands quite a lot of knowledge of the Model.
Step 5 essentially provides finitely many tests as support for the correctness of an infinite
quantification.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 36 / 58
72. Proof Explanation
Conceptual Modelling from a Logical Point of View
1 Observe the “World”.
2 Determine what is relevant.
3 Choose/Define your terminology (non-logical linguistic terms).
4 Write down the main laws governing your “World” (Axioms).
5 Verify the correctness (sometimes completeness too) of your set of Laws.
Steps 1 and 2 may be facilitated by the use of an informal notation (UML, ER, FlowCharts,
etc) and their respective methodology, but it is essentially “Black Art” (cf. Maibaum).
Step 5 full-filling demands quite a lot of knowledge of the Model.
Step 5 essentially provides finitely many tests as support for the correctness of an infinite
quantification.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 36 / 58
73. Proof Explanation
Conceptual Modelling from a Logical Point of View
1 Observe the “World”.
2 Determine what is relevant.
3 Choose/Define your terminology (non-logical linguistic terms).
4 Write down the main laws governing your “World” (Axioms).
5 Verify the correctness (sometimes completeness too) of your set of Laws.
Steps 1 and 2 may be facilitated by the use of an informal notation (UML, ER, FlowCharts,
etc) and their respective methodology, but it is essentially “Black Art” (cf. Maibaum).
Step 5 full-filling demands quite a lot of knowledge of the Model.
Step 5 essentially provides finitely many tests as support for the correctness of an infinite
quantification.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 36 / 58
74. Proof Explanation
Conceptual Modelling from a Logical Point of View
1 Observe the “World”.
2 Determine what is relevant.
3 Choose/Define your terminology (non-logical linguistic terms).
4 Write down the main laws governing your “World” (Axioms).
5 Verify the correctness (sometimes completeness too) of your set of Laws.
Steps 1 and 2 may be facilitated by the use of an informal notation (UML, ER, FlowCharts,
etc) and their respective methodology, but it is essentially “Black Art” (cf. Maibaum).
Step 5 full-filling demands quite a lot of knowledge of the Model.
Step 5 essentially provides finitely many tests as support for the correctness of an infinite
quantification.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 36 / 58
75. Proof Explanation
Conceptual Modelling from a Logical Point of View
1 Observe the “World”.
2 Determine what is relevant.
3 Choose/Define your terminology (non-logical linguistic terms).
4 Write down the main laws governing your “World” (Axioms).
5 Verify the correctness (sometimes completeness too) of your set of Laws.
Steps 1 and 2 may be facilitated by the use of an informal notation (UML, ER, FlowCharts,
etc) and their respective methodology, but it is essentially “Black Art” (cf. Maibaum).
Step 5 full-filling demands quite a lot of knowledge of the Model.
Step 5 essentially provides finitely many tests as support for the correctness of an infinite
quantification.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 36 / 58
76. Proof Explanation
Conceptual Modelling from a Logical Point of View
1 Observe the “World”.
2 Determine what is relevant.
3 Choose/Define your terminology (non-logical linguistic terms).
4 Write down the main laws governing your “World” (Axioms).
5 Verify the correctness (sometimes completeness too) of your set of Laws.
Steps 1 and 2 may be facilitated by the use of an informal notation (UML, ER, FlowCharts,
etc) and their respective methodology, but it is essentially “Black Art” (cf. Maibaum).
Step 5 full-filling demands quite a lot of knowledge of the Model.
Step 5 essentially provides finitely many tests as support for the correctness of an infinite
quantification.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 36 / 58
77. Proof Explanation
Conceptual Modelling from a Logical Point of View
1 Observe the “World”.
2 Determine what is relevant.
3 Choose/Define your terminology (non-logical linguistic terms).
4 Write down the main laws governing your “World” (Axioms).
5 Verify the correctness (sometimes completeness too) of your set of Laws.
Steps 1 and 2 may be facilitated by the use of an informal notation (UML, ER, FlowCharts,
etc) and their respective methodology, but it is essentially “Black Art” (cf. Maibaum).
Step 5 full-filling demands quite a lot of knowledge of the Model.
Step 5 essentially provides finitely many tests as support for the correctness of an infinite
quantification.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 36 / 58
78. Proof Explanation
Positives, False Negatives, False Positives
Is anything true about Truth?
M |= φ and Spec(M) φ.
Why is φ truth? Provide me a proof of φ.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 37 / 58
79. Proof Explanation
Positives, False Negatives, False Positives
Is anything true about Truth?
M |= φ and Spec(M) φ.
Why is φ truth? Provide me a proof of φ.
Is anything wrong with the Truth?
M |= φ, but Spec(M) |= φ.
A counter-model is found. Why is this a counter-model?
Model-Checking based reasoning is of great help!
Explanations from counter-examples.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 37 / 58
80. Proof Explanation
Positives, False Negatives, False Positives
Is anything true about Truth?
M |= φ and Spec(M) φ.
Why is φ truth? Provide me a proof of φ.
Is anything wrong with the Truth?
M |= φ, but Spec(M) |= φ.
A counter-model is found. Why is this a counter-model?
Model-Checking based reasoning is of great help!
Explanations from counter-examples.
Is anything true about Falsity?
M |= φ, but Spec(M) φ.
Why does this false proposition hold? Provide me a proof of φ.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 37 / 58
81. Proof Explanation
Existing Deductive Systems Paradigms
1 Aristotle’s Syllogisms (300 B.C.)
2 Axiomatic (Frege1879, Hilbert, Russell).
3 Natural Deduction (Jaskowski1929,Gentzen1934-5, Prawitz1965)
4 Sequent Calculus (Gentzen1934-5)
5 Tableaux (Beth 1955, Smullyan1964)
6 Resolution-Based (A.Robinson1965)
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 38 / 58
82. Proof Explanation
Fundamental facts on Automating SC and ND
Analyticity
Every proof of Γ α has only occurrences of sub-formulas of Γ
and α (Sub-formula Principle SFP).
Cut-Elimination in SC entails SFP.
Normalization in ND entails SFP.
Strongly related to analytic Tableaux based procedures.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 39 / 58
83. Proof Explanation
Fundamental facts on Automating SC and ND
Analyticity
Every proof of Γ α has only occurrences of sub-formulas of Γ
and α (Sub-formula Principle SFP).
Cut-Elimination in SC entails SFP.
Normalization in ND entails SFP.
Strongly related to analytic Tableaux based procedures.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 39 / 58
84. Proof Explanation
Fundamental facts on Automating SC and ND
Analyticity
Every proof of Γ α has only occurrences of sub-formulas of Γ
and α (Sub-formula Principle SFP).
Cut-Elimination in SC entails SFP.
Normalization in ND entails SFP.
Strongly related to analytic Tableaux based procedures.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 39 / 58
85. Proof Explanation
Fundamental facts on Automating SC and ND
Analyticity
Every proof of Γ α has only occurrences of sub-formulas of Γ
and α (Sub-formula Principle SFP).
Cut-Elimination in SC entails SFP.
Normalization in ND entails SFP.
Strongly related to analytic Tableaux based procedures.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 39 / 58
86. Proof Explanation
Proof Explanation: general ideas
The generation of an explanatory text from a formal proof is still
under investigation by the community.
The use of anaphoras (linguistic reference to an antecedent piece
of text) and cataphoras (linguistic reference to a posterior piece of
text) in producing explanations is a must.
Unstructured nesting of endophoras is hard to follow.
As more structured the proof is, as easier the generation of a
better text, at least concerning the use of endophoras.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 40 / 58
87. Proof Explanation
Example 1/2
Doctor ⇒ Rich, Doctor
-r
Doctor ⇒ (Rich Doctor )
∀child ∀child
prom-∀
Doctor ⇒ (Rich Doctor )
weak-l
, ∀child Doctor ⇒ ∀child (Rich Doctor )
∃child ∀child
¬-r
⇒ ¬Doctor , (Rich Doctor )
weak-r
⇒ ∃child ¬Doctor , ∃child Lawyer , ∀child (Rich Doctor )
∃child ∀child
∃-r
⇒ ¬Doctor , ∃child.Lawyer , (Rich Doctor )
∃-r
⇒ ∃child.¬Doctor , ∃child.Lawyer , ∀child (Rich Doctor )
-r
⇒ (∃child.¬Doctor ) (∃child.Lawyer ), ∀child (Rich Doctor )
∃child
prom-∃
⇒ ∃child ((∃child.¬Doctor ) (∃child.Lawyer )), ∃child,∀child (Rich Doctor )
∃child
¬-l
, ∀child ¬((∃child.¬Doctor ) (∃child.Lawyer )) ⇒ ∃child,∀child (Rich Doctor )
∃child
∀-r
, ∀child ¬((∃child.¬Doctor ) (∃child.Lawyer )) ⇒ ∃child ∀child.(Rich Doctor )
∃child
∀-l
, ∀child.¬((∃child.¬Doctor ) (∃child.Lawyer )) ⇒ ∃child ∀child.(Rich Doctor )
∃child
∃-r
, ∀child.¬((∃child.¬Doctor ) (∃child.Lawyer )) ⇒ ∃child.∀child.(Rich Doctor )
∃child. , ∀child.¬((∃child.¬Doctor ) (∃child.Lawyer )) ⇒ ∃child.∀child.(Rich Doctor )
∃-l
∃child. ∀child.¬((∃child.¬Doctor ) (∃child.Lawyer )) ⇒ ∃child.∀child.(Rich Doctor )
-l
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 41 / 58
88. Proof Explanation
Example 2/2
The explanation below was build from top to bottom, by a procedure
that tries to not repeat conjunctive particles:
1 Doctors are Doctors or Rich
2 So, Everyone having all children Doctors has all children Doctors or Rich.
3 Hence, everyone either has at least a child that is not a doctor or every children is a doctor
or rich.
4 Moreover, everyone is of the kind above, or, alternatively, have at least one child that is a
lawyer.
5 In other words, if everyone has at least one child, then it has one child that has at least one
child that is a lawyer, or at least one child that is not a doctor, or have all children doctors or
rich.
6 Thus, whoever has all children not having at least one child not a doctor or at least one
child lawyer has at least one child having every children doctors or rich.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 42 / 58
89. Proof Explanation
Arguments in favour of Natural Deduction as a basis
for theorem explanation
Common Sense and Intuitive reasons
“Fewer” proofs of a proposition when compared to other Deductive
Systems.
“More” structure and existence of specific patterns to help paragraph
construction in NL.
Working hypothesis: “Optimal explanations should be tailored from
well-known proof patterns”
Technical reasons
Natural Deduction reveals the computational content of a proof.
The prover can choose the pattern it wants the proof should have
(Seldin, Prawitz).
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 43 / 58
90. Proof Explanation
Arguments in favour of Natural Deduction as a basis
for theorem explanation
Common Sense and Intuitive reasons
“Fewer” proofs of a proposition when compared to other Deductive
Systems.
“More” structure and existence of specific patterns to help paragraph
construction in NL.
Working hypothesis: “Optimal explanations should be tailored from
well-known proof patterns”
Technical reasons
Natural Deduction reveals the computational content of a proof.
The prover can choose the pattern it wants the proof should have
(Seldin, Prawitz).
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 43 / 58
91. Proof Explanation
Arguments in favour of Natural Deduction as a basis
for theorem explanation
Common Sense and Intuitive reasons
“Fewer” proofs of a proposition when compared to other Deductive
Systems.
“More” structure and existence of specific patterns to help paragraph
construction in NL.
Working hypothesis: “Optimal explanations should be tailored from
well-known proof patterns”
Technical reasons
Natural Deduction reveals the computational content of a proof.
The prover can choose the pattern it wants the proof should have
(Seldin, Prawitz).
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 43 / 58
92. Proof Explanation
Arguments in favour of Natural Deduction as a basis
for theorem explanation
Common Sense and Intuitive reasons
“Fewer” proofs of a proposition when compared to other Deductive
Systems.
“More” structure and existence of specific patterns to help paragraph
construction in NL.
Working hypothesis: “Optimal explanations should be tailored from
well-known proof patterns”
Technical reasons
Natural Deduction reveals the computational content of a proof.
The prover can choose the pattern it wants the proof should have
(Seldin, Prawitz).
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 43 / 58
93. Reasoining UML in NDALCQI
Conceptual Modelling in UML and ER
The Informal Side
Graphical notations seem to be adequate to the human being
understanding and manipulation.
Lacking of a formal consistency checking.
The Logical Side
FOL cannot provide checking of KB consistency.
Decidable logics seems to be more adequate.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 44 / 58
94. Reasoining UML in NDALCQI
Conceptual Modelling in UML and ER
The Informal Side
Graphical notations seem to be adequate to the human being
understanding and manipulation.
Lacking of a formal consistency checking.
The Logical Side
FOL cannot provide checking of KB consistency.
Decidable logics seems to be more adequate.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 44 / 58
95. Reasoining UML in NDALCQI
Conceptual Modelling in UML and ER
The Informal Side
Graphical notations seem to be adequate to the human being
understanding and manipulation.
Lacking of a formal consistency checking.
The Logical Side
FOL cannot provide checking of KB consistency.
Decidable logics seems to be more adequate.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 44 / 58
96. Reasoining UML in NDALCQI
Conceptual Modelling in UML and ER
The Informal Side
Graphical notations seem to be adequate to the human being
understanding and manipulation.
Lacking of a formal consistency checking.
The Logical Side
FOL cannot provide checking of KB consistency.
Decidable logics seems to be more adequate.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 44 / 58
97. Reasoining UML in NDALCQI
Conceptual Modelling in UML and ER
The Informal Side
Graphical notations seem to be adequate to the human being
understanding and manipulation.
Lacking of a formal consistency checking.
The Logical Side
FOL cannot provide checking of KB consistency.
Decidable logics seems to be more adequate.
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 44 / 58
98. Reasoining UML in NDALCQI
Explaining Theorems on the Conceptual Modelling
Domain
A Case Study in UML
1 Why UML? ⇒ It is complex (UML consistency is
EXPTIME-Complete), useful and popular.
2 What do we need?
A Logical Language to express properties and their proofs
(ALCQI)
A Good (Normalizable) Natural Deduction for ALCQI
Proof Patterns that yield good explanation (to come...)
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 45 / 58
99. Reasoining UML in NDALCQI
Explaining Theorems on the Conceptual Modelling
Domain
A Case Study in UML
1 Why UML? ⇒ It is complex (UML consistency is
EXPTIME-Complete), useful and popular.
2 What do we need?
A Logical Language to express properties and their proofs
(ALCQI)
A Good (Normalizable) Natural Deduction for ALCQI
Proof Patterns that yield good explanation (to come...)
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 45 / 58
100. Reasoining UML in NDALCQI
Explaining Theorems on the Conceptual Modelling
Domain
A Case Study in UML
1 Why UML? ⇒ It is complex (UML consistency is
EXPTIME-Complete), useful and popular.
2 What do we need?
A Logical Language to express properties and their proofs
(ALCQI)
A Good (Normalizable) Natural Deduction for ALCQI
Proof Patterns that yield good explanation (to come...)
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 45 / 58
101. Reasoining UML in NDALCQI
Explaining Theorems on the Conceptual Modelling
Domain
A Case Study in UML
1 Why UML? ⇒ It is complex (UML consistency is
EXPTIME-Complete), useful and popular.
2 What do we need?
A Logical Language to express properties and their proofs
(ALCQI)
A Good (Normalizable) Natural Deduction for ALCQI
Proof Patterns that yield good explanation (to come...)
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 45 / 58
102. Reasoining UML in NDALCQI
Explaining Theorems on the Conceptual Modelling
Domain
A Case Study in UML
1 Why UML? ⇒ It is complex (UML consistency is
EXPTIME-Complete), useful and popular.
2 What do we need?
A Logical Language to express properties and their proofs
(ALCQI)
A Good (Normalizable) Natural Deduction for ALCQI
Proof Patterns that yield good explanation (to come...)
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 45 / 58
103. Reasoining UML in NDALCQI
Explaining Theorems on the Conceptual Modelling
Domain
A Case Study in UML
1 Why UML? ⇒ It is complex (UML consistency is
EXPTIME-Complete), useful and popular.
2 What do we need?
A Logical Language to express properties and their proofs
(ALCQI)
A Good (Normalizable) Natural Deduction for ALCQI
Proof Patterns that yield good explanation (to come...)
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 45 / 58
104. Reasoining UML in NDALCQI
ALCQI KB related to UML Class Diagram
[BerCalvGiac2005]
D. Berardi et al. / Artificial Intelligence 168 (2005) 70–118 81
Fig. 12. UML class diagram of Example 2.5.
Origin ∀place.String
2.4. Origin constraints
General ∃place. (≤ 1 place)
Origin ∃call.PhoneCall (≤ 1 call) ∃from.Phone (≤ 1 from)
Disjointness and covering constraints (≤ 1call) ∃from.CellPhone used 1 from)
MobileOrigin ∃call.MobileCall are in practice the most commonly (≤ con-
straints in UML class diagrams. However, UML allows for other forms of constraints,
PhoneCall (≥ 1 call− .Origin) (≤ 1 call− .Origin)
specifying class identifiers, functional dependencies for associations, and, more generally
−
through the use of ∀reference .PhoneBill ∀reference.PhoneCall
OCL [8], any form of constraint expressible in FOL. Note that, due
−
to their expressive (≥ 1 reference ) could in fact be used to express the semantics
PhoneBill power, OCL constraints
PhoneCall
of the standard UML class diagram constructs. reference)
(≥ 1 reference) (≤ 1 This is an indication that a liberal use of
MobileCall PhoneCall
OCL constraints can actually compromise the understandability of the diagram. Hence,
MobileOrigin Origin
the use of constraints is typically limited. Also, unrestricted use of OCL constraints makes
CellPhone a class diagram undecidable, since it amounts to full FOL reasoning. In the
reasoning on Phone
FixedPhonewe will not consider general constraints.
following, Phone
¬FixedPhone
We conclude the section with an example of a full UML class diagram.
CellPhone
Phone CellPhone FixedPhone
Example 2.5. Fig. 12 shows a complete UML class diagram that models phone calls origi-
nating from different kinds of phones, and phone bills they belong to.13 The diagram shows
that a MobileCall is a particular kind of PhoneCall and that the Origin of each PhoneCall
is one and only one Phone. Additionally, a Phone can be only of two different kinds: a
Alexandre Rademaker ()
FixedPhone or a CellPhone. Proof Theory for Description Logics
On the Mobile calls originate (through the association MobileOrigin)March 30, 2010 46 / 58
105. Reasoining UML in NDALCQI
Example: A Negative Testing
An (incorrect) generalization (a CellPhone is a FixedPhone) is
introduced in the KB.
CellPhone FixedPhone is added to KB.
CellPhone is empty (inconsistent)
Cell ¬Fixed [Cell]1 Cell Fixed [Cell]1
¬Fixed Fixed
⊥ 1
Cell ⊥
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 47 / 58
106. Reasoining UML in NDALCQI
Example: A False Positive in the new KB
In the modified diagram, Phone ≡ FixedPhone can be drawn. This
is not directly proved from the inconsistency of CellPhone.
It is shown that Phone FixedPhone since FixedPhone Phone
is already an axiom of KB.
[Phone]1 Phone Cell Fixed [Cell] Cell Fixed
Cell Fixed Fixed [Fixed]
Fixed 1
Phone Fixed
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 48 / 58
107. Reasoining UML in NDALCQI
Example: A False Positive yielding a refining of KB
MobileCall participates on the association MobileOrigin with
multiplicity 0..1, instead of the 0..* presented in the UML diagram.
[MC]1 MC PC
MO O PC PC ≥ 1 c− .O ≤ 1 c− .O
−
[≥ 2 c .MO] 2
≥ 2 c− .MO ≥ 2 c− .O ≥ 1 c− .O ≤ 1 c− .O
≥ 2 c− .O ≤ 1 c− .O
⊥ 2
¬ ≥ 2 c− .MO
1
MC ¬ ≥ 2 c− .MO
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 49 / 58
108. The prototype theorem prover
The language
fmod SYNTAX is
inc NAT .
sorts AConcept Concept ARole Role .
subsort AConcept Concept .
subsort ARole Role .
ops ALL EXIST : Role Concept - Concept .
ops CTRUE CFALSE : - AConcept .
op __ : Concept Concept - Concept [ctor gather (e E) prec 31] .
op _|_ : Concept Concept - Concept [ctor gather (e E) prec 32] .
op ~_ : Concept - Concept [ctor prec 30] .
eq ~ CTRUE = CFALSE .
eq ~ CFALSE = CTRUE .
endfm
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 50 / 58
109. The prototype theorem prover
The sequent calculus
fmod SEQUENT-CALCULUS is
inc LALC-SYNTAX .
inc SET{Expression} .
inc SET{Label} .
...
sorts Sequent Goal State Proof .
subsort Goal State Proof .
op next : Nat - State .
op goals : Set{Nat} - State .
op [_from_by_is_] : Nat Nat Qid Sequent - Goal [ctor] .
op nil : - Proof [ctor] .
op __ : Proof Proof - Proof [ctor comm assoc] .
op _|-_ : Set{Expression} Set{Expression} -
Sequent [ctor prec 122 gather(e e)] .
...
endfm
Alexandre Rademaker () On the Proof Theory for Description Logics March 30, 2010 51 / 58