A Subatomic Proof System for Decision Trees

被引:0
作者
Barrett, Chris [1 ]
Guglielmi, Alessio [1 ]
机构
[1] Univ Bath, Dept Comp Sci, Bath BA2 7AY, Avon, England
基金
英国工程与自然科学研究理事会;
关键词
Deep inference; open deduction; subatomic logic; cut elimination; Statman tautologies; CALCULUS;
D O I
10.1145/3545116
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
We design a proof system for propositional classical logic that integrates two languages for Boolean functions: standard conjunction-disjunction-negation and binary decision trees. We give two reasons to do so. The first is proof-theoretical naturalness: The system consists of all and only the inference rules generated by the single, simple, linear scheme of the recently introduced subatomic logic. Thanks to this regularity, cuts are eliminated via a natural construction. The second reason is that the system generates efficient proofs. Indeed, we showthat a certain class of tautologies due to Statman, which cannot have better than exponential cut-free proofs in the sequent calculus, have polynomial cut-free proofs in our system. We achieve this by using the same construction that we use for cut elimination. In summary, by expanding the language of propositional logic, we make its proof theory more regular and generate more proofs, some of which are very efficient. That design is made possible by considering atoms as superpositions of their truth values, which are connected by self-dual, non-commutative connectives. A proof can then be projected via each atom into two proofs, one for each truth value, without a need for cuts. Those projections are semantically natural and are at the heart of the constructions in this article. To accommodate self-dual non-commutativity, we compose proofs in deep inference.
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页数:25
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共 21 条
  • [1] Boolean expression diagrams
    Andersen, HR
    Hulgaard, H
    [J]. 12TH ANNUAL IEEE SYMPOSIUM ON LOGIC IN COMPUTER SCIENCE, PROCEEDINGS, 1997, : 88 - 98
  • [2] Cut elimination inside a deep inference system for classical predicate logic
    Brünnler K.
    [J]. Studia Logica, 2006, 82 (1) : 51 - 71
  • [3] Brunnler Kai, 2001, LECT NOTES COMPUTER, V2250, P347, DOI DOI 10.1007/3-540-45653-8
  • [4] Bruscoli P, 2016, LOG METH COMPUT SCI, V12, DOI [10.2168/LMCS-12(1:5)2016, 10.1007/978-3-642-17511-4_9]
  • [5] On the Proof Complexity of Deep Inference
    Bruscoli, Paola
    Guglielmi, Alessio
    [J]. ACM TRANSACTIONS ON COMPUTATIONAL LOGIC, 2009, 10 (02)
  • [6] Buss Sam, 2020, P 28 EACSL ANN C COM, V12, P1, DOI [10.4230/LIPIcs.CSL.2020.12, DOI 10.4230/LIPICS.CSL.2020.12]
  • [7] Clote Peter, 2002, BOOLEAN FUNCTIONS CO, DOI DOI 10.1007/978-3-662-04943-3
  • [8] Das A, 2011, LECT NOTES ARTIF INT, V6793, P134, DOI 10.1007/978-3-642-22119-4_12
  • [9] LINEAR LOGIC
    GIRARD, JY
    [J]. THEORETICAL COMPUTER SCIENCE, 1987, 50 (01) : 1 - 102
  • [10] Guglielmi A., 2001, Computer Science Logic. 15th International Workshop, CSL 2001 10th Annual Conference of the EACSL. Proceedings (Lecture Notes in Computer Science Vol.2142), P54