• DocumentCode
    2318909
  • Title

    Automated theorem finding by forward deduction based on strong relevant logic: A case study in NBG set theory

  • Author

    Gao, Hongbiao ; Shi, Kai ; Goto, Yuichi ; Cheng, Jingde

  • Author_Institution
    Dept. of Inf. & Comput. Sci., Saitama Univ., Saitama, Japan
  • Volume
    5
  • fYear
    2012
  • fDate
    15-17 July 2012
  • Firstpage
    1859
  • Lastpage
    1865
  • Abstract
    The problem of automated theorem finding is one of 33 basic research problems in automated reasoning which was originally proposed by Wos in 1988, and it is still an open problem. To solve the problem, a forward deduction approach based on the strong relevant logics was proposed. To verify the effectiveness of the approach, this paper presents a case study of automated theorem finding in NBG set theory by forward deduction based on the strong relevant logics. The ultimate goal of automated theorem finding in NBG set theory is to find new and interesting theorems. As the first step, this case study tries to do “rediscovery” in NBG set theory, i.e., to deduce already proved theorems from axioms, definitions and /or other theorems of NBG set theory. However, from the viewpoint of the mechanism of deducing theorems, “re-discovery” is as same as “discovery”. The paper shows several known theorems rediscovered successfully by the approach. The paper also shows issues of the approach for real “discovery”.
  • Keywords
    formal logic; inference mechanisms; set theory; NBG set theory; automated reasoning; automated theorem finding; basic research problems; forward deduction; strong relevant logic; Abstracts; Barium; Automated theorem finding; Forward deduction; NBG set theory; Strong relevant logic;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2012 International Conference on
  • Conference_Location
    Xian
  • ISSN
    2160-133X
  • Print_ISBN
    978-1-4673-1484-8
  • Type

    conf

  • DOI
    10.1109/ICMLC.2012.6359659
  • Filename
    6359659