AN ARGUMENT‐BASED APPROACH TO NONMONOTONIC REASONING * | Zendy

LIN FANGZHEN | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Premium

AN ARGUMENT‐BASED APPROACH TO NONMONOTONIC REASONING *

Author(s) -

LIN FANGZHEN

Publication year - 1993

Publication title -

computational intelligence

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.353

H-Index - 52

eISSN - 1467-8640

pISSN - 0824-7935

DOI - 10.1111/j.1467-8640.1993.tb00309.x

Subject(s) - argument (complex analysis) , completeness (order theory) , inference , negation , non monotonic logic , mathematics , set (abstract data type) , rule of inference , computer science , artificial intelligence , programming language , mathematical analysis , biochemistry , chemistry

We define an argument system to be a pair consisting of a set of inference rules and a set of completeness conditions. Inference rules are used to build arguments. Completeness conditions are used to define argument structures, which are sets of arguments supporting belief sets. We reformulate Reiter's default logic as special argument systems. This enables us, among other things, to apply the negation‐as‐failure rule to general default theories. We also speculate on some other potential uses of our argument systems.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here

Accelerating Research