Abstract
Abstract One of key issues for α-n(t) ary resolution automated reasoning based on lattice-valued logic with truth-value in a lattice implication algebra is to investigate the α-n(t) ary resolution of some generalized literals. In this article, the determination of α-resolution of any 3-ary generalized literals which include the implication operators not more than 2 in LP(X). It not only lay the foundation for practical implementation of automated reasoning algorithm in LP(X), but also provides the strong support for α-n(t) ary resolution automated reasoning approaches.
Highlights
As is known to all, one significant function of artificial intelligence is to make computer simulate human being in dealing with uncertain information
In order to investigate a many-valued logical system whose propositional value is given in a lattice, in 1993, Xu first established the lattice implication algebra by
With the development of research, it shows that α-2 ary resolution automated reasoning based on lattice-valued logic aiming at processing uncertain information with incomparability is scientific and effective
Summary
As is known to all, one significant function of artificial intelligence is to make computer simulate human being in dealing with uncertain information. The α-resolution is called α-2 ary resolution; (c) it is not easy to judge directly if two generalized literals are α-resolvent or not, because the structure of generalized literal is very complex Due to these new features, it is not feasible to apply directly the resolution-based automated reasoning theory and methods in classical logic and in many chain-type many-valued logics into that of lattice-valued logic with incomparability. With the development of research, it shows that α-2 ary resolution automated reasoning based on lattice-valued logic aiming at processing uncertain information with incomparability is scientific and effective. It is necessary to study resolution automated reasoning theory, methods, algorithms and procedures which improve the resolution automated reasoning efficiency under the premise of keeping the depict ability in complexity problems To resolve these limitations, Xu 18 extended the number of resolution generalized literal from 2 to n, and proposed the general form of α-resolution, and the soundness and completeness are built. It will be further to lay the foundation on researching α-n(t) ary resolution automated reasoning
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