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2. 1. Task & Known results
2. Brief methodology of the proof
1. Cut elimination
2. Contraction elimination
3. → 𝐿 elimination
4. Proof of strictly-decreasingness
3. Implementation detail
4. Further implementation plan
3. Task
• Proposition: 𝐴𝑡𝑜𝑚 𝑛 , ∧, ∨, →, ⊥
• Task: Is given propositional formula P provable
in LJ?
– It’s known to be decidable. [Dyckhoff]
• This talk: how to prove this decidability on
Coq
4. Known results
• Decision problem on IPC is PSPACE complete
[Statman]
– Especially, O(N log N) space decision procedure is
known [Hudelmaier]
• These approaches are backtracking on LJ
syntax.
5. Known results
• cf. classical counterpart of this problem is
co-NP complete.
– Proof: find counterexample in boolean-valued
semantics (SAT).
6. methodology
• To prove decidability, all rules should be
strictly decreasing on some measuring.
𝑆1 ,𝑆2 ,…,𝑆 𝑁
• More formally, for all rules 𝑟𝑢𝑙𝑒
𝑆0
and all number 𝑖 (1 ≤ 𝑖 ≤ 𝑁),
𝑆 𝑖 < 𝑆0
on certain well-founded relation <.
7. methodology
1. Eliminate cut rule of LJ
2. Eliminate contraction rule
3. Split → 𝑳 rule into 4 pieces
4. Prove that every rule is strictly decreasing
11. Cut elimination
• 2. Prove the general cut rule
Γ ⊢ 𝐴 𝐴 𝑛 , Δ ⊢ 𝐺
𝑐𝑢𝑡𝐺
Γ, Δ ⊢ 𝐺
by induction on the size of 𝐴
and proof structure of the right hand.
• 3. specialize 𝑐𝑢𝑡𝐺 (n = 1) ■
22. Correctness of Terminating LJ
• 1. If Γ ⊢ 𝐺 is provable in Contraction-free LJ,
At least one of these is true:
– Γ includes ⊥, 𝐴 ∧ 𝐵, or 𝐴 ∨ 𝐵
– Γ includes both 𝐴𝑡𝑜𝑚(𝑛) and 𝐴𝑡𝑜𝑚 𝑛 → 𝐵
– Γ ⊢ 𝐺 has a proof whose bottommost rule is not
the form of
𝐴𝑡𝑜𝑚 𝑛 →𝐵,𝐴𝑡𝑜𝑚 𝑛 ,Γ⊢𝐴𝑡𝑜𝑚 𝑛 𝐵,𝐴𝑡𝑜𝑚 𝑛 ,Γ⊢𝐺
(→ 𝐿 )
𝐴𝑡𝑜𝑚 𝑛 →𝐵,𝐴𝑡𝑜𝑚(𝑛),Γ⊢𝐺
• Proof: induction on proof structure
23. Correctness of Terminating LJ
• 2. every sequent provable in Contraction-free
LJ is also provable in Terminating LJ.
• Proof: induction by size of the sequent.
– Size: we will introduce later
26. Proof of termination
• ordering of Proposition List
– Use Multiset ordering (Dershowitz and Manna
ordering)
27. Multiset Ordering
• Multiset Ordering: a binary relation between
multisets (not necessarily be ordering)
• 𝐴> 𝐵⇔ Not empty
A
B
28. Multiset Ordering
• If 𝑅 is a well-founded binary relation, the
Multiset Ordering over 𝑅 is also well-founded.
• Well-founded: every element is accessible
• 𝐴 is accessible : every element 𝐵 such that
𝐵 < 𝐴 is accessible
29. Multiset Ordering
Proof
• 1. induction on list
• Nil ⇒ there is no 𝐴 such that 𝐴 < 𝑀 Nil,
therefore it’s accessible.
• We will prove: 𝐴𝑐𝑐 𝑀 𝐿 ⇒ 𝐴𝑐𝑐 𝑀 (𝑥 ∷ 𝐿)
30. Multiset Ordering
• 2. duplicate assumption
• Using 𝐴𝑐𝑐(𝑥) and 𝐴𝑐𝑐 𝑀 (𝐿), we will prove
𝐴𝑐𝑐 𝑀 𝐿 ⇒ 𝐴𝑐𝑐 𝑀 (𝑥 ∷ 𝐿)
• 3. induction on 𝑥 and 𝐿
– We can use these two inductive hypotheses.
1. ∀𝐾 𝑦, 𝑦 < 𝑥 ⇒ 𝐴𝑐𝑐 𝑀 𝐾 ⇒ 𝐴𝑐𝑐 𝑀 (𝑦 ∷ 𝐾)
2. ∀𝐾, 𝐾 < 𝑀 𝐿 ⇒ 𝐴𝑐𝑐 𝑀 𝐾 ⇒ 𝐴𝑐𝑐 𝑀 (𝑥 ∷ 𝐾)
31. Multiset Ordering
• 4. Case Analysis
• By definition, 𝐴𝑐𝑐 𝑀 (𝑥 ∷ 𝐿) is equivalent to
∀𝐾, 𝐾 < 𝑀 (𝑥 ∷ 𝐿) ⇒ 𝐴𝑐𝑐 𝑀 (𝐾)
• And there are 3 patterns:
1. 𝐾 includes 𝑥
2. 𝐾 includes 𝑦s s.t. 𝑦 < 𝑥, and 𝐾 minus all such 𝑦 is
equal to 𝐿
3. 𝐾 includes 𝑦s s.t. 𝑦 < 𝑥, and 𝐾 minus all such 𝑦 is
less than 𝐿
• Each pattern is proved using the Inductive
Hypotheses.
40. Further implementation plan
• Refactoring (1) : improve Permutation-
associated tactics
– A smarter auto-unifying tactics is needed
– Write tactics using Objective Caml
• Refactoring (2) : use Ssreflect tacticals
– This makes the proof more manageable
41. Further implementation plan
• Refactoring (3) : change proof order
– Contraction first, cut next
– It will make the proof shorter
• Refactoring (4) : discard Multiset Ordering
– If we choose appropriate weight function of
Propositional Formula, we don’t need Multiset
Ordering. (See [Hudelmaier])
– It also enables us to analyze complexity of this
procedure
42. Further implementation plan
• Refactoring (5) : Proof of completeness
– Now completeness theorem depends on the
decidability
• New Theorem (1) : Other Syntaxes
– NJ and HJ may be introduced
• New Theorem (2) : Other Semantics
– Heyting Algebra
43. Further implementation plan
• New Theorem (3) : Other decision procedure
– Decision procedure using semantics (if any)
– More efficient decision procedure (especially
𝑂(𝑁 log 𝑁)-space decision procedure)
• New Theorem (4) : Complexity
– Proof of PSPACE-completeness