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.
引用
收藏
页数:25
相关论文
共 50 条
  • [21] DECISION TREES
    GARBUTT, D
    CHEMISTRY & INDUSTRY, 1970, (29) : 938 - &
  • [22] Decision trees
    Coadou, Yann
    SOS 08: IN2P3 SCHOOL OF STATISTICS, 2010, 4
  • [23] DECISION TREES
    FOTR, J
    EKONOMICKO-MATEMATICKY OBZOR, 1975, 11 (02): : 142 - 161
  • [24] Decision trees
    de Ville, Barry
    WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS, 2013, 5 (06): : 448 - 455
  • [25] DECISION TREES
    CONCHA, SR
    TRIAL, 1984, 20 (10): : 6 - 6
  • [26] A comparative study of pruned decision trees and fuzzy decision trees
    Benbrahim, H
    Bensaid, A
    PEACHFUZZ 2000 : 19TH INTERNATIONAL CONFERENCE OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY - NAFIPS, 2000, : 227 - 231
  • [27] MAPTree: Beating "Optimal" Decision Trees with Bayesian Decision Trees
    Sullivan, Colin
    Tiwari, Mo
    Thrun, Sebastian
    THIRTY-EIGHTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 38 NO 8, 2024, : 9019 - 9026
  • [28] Using Decision Trees as an Expert System for Clinical Decision Support for COVID-19
    Chrimes, Dillon
    INTERACTIVE JOURNAL OF MEDICAL RESEARCH, 2023, 12
  • [29] Farm Decision Support System(FDSS) with various environmental factors using Decision Trees
    Keerthana, S. M.
    Bharathi, R. Elakkiya
    Sherlin, S. Ashna
    2024 5TH INTERNATIONAL CONFERENCE ON INNOVATIVE TRENDS IN INFORMATION TECHNOLOGY, ICITIIT 2024, 2024,
  • [30] MikiBeta: A General GUI Library for Visualizing Proof Trees System Description and Demonstration
    Sakurai, Kanako
    Asai, Kenichi
    LOGIC-BASED PROGRAM SYNTHESIS AND TRANSFORMATION, 2011, 6564 : 84 - 98