Resolution-based Automated Reasoning In Linguistic 2-Tuple

Artificial intelligence is a discipline that enables computers to simulate certain thinking processes and intelligent behaviors of people,and creates computers that are similar to human brain intelligence so that computers can achieve higher-level applications.The language of human beings in real life is ever-changing,so that the requirement for the integrity of information,and computers simulations of human intelligence conduct reasoning.In expression of human language,the linguistic 2-tuple can accurately describe the language information,making it greatly reduce the lack of information in computational reasoning.As a significant branch of automated reasoning,resolution principle has been widely concerned by scholars because of its concise reasoning process.Based on the research of the linguistic 2-tuple,this paper combines the propositional logic and the first-order logic,establishes the linguistic 2-tuple propositional logic system and the linguistic 2-tuple first-order logic system.This paper proposes a generalized semantic resolution method based on linguistic 2-tuple propositional logic and a generalized lock resolution method based on linguistic 2-tuple first-order logic,by combing semantic resolution strategy and lock resolution strategy.The main results of this paper are shown as follows:This paper proposes a linguistic 2-tuple propositional logic system based on the classical logic and linguistic 2-tuple.On this basis,combines semantic resolution to form the generalized semantic resolution method based on linguistic 2-tuple propositional logic.In this system,every linguistic 2-tuple propositional logic formula can be transformed into linguistic 2-tuple propositional logic generalized clause.According to the linguistic 2-tuple propositional logic literal's satisfiability,we judge whether each linguistic 2-tuple propositional logic literal is satisfiable or not,thus,the linguistic 2-tuple propositional logic literal can be divided into two classes,i.e.linguistic 2-tuple propositional logic similar literals and linguistic 2-tuple propositional logic complementary literals.According to semantics,the linguistic 2-tuple propositional logic generalized clauses can be divided into two classes,stipulated that clauses in each part are not allowed to be resolution.At the same time,this paper also introduces the word order,which specifies that one of the clauses in the resolution clause can only be the literal with the largest order in the clause,and can be used to reduce the number of possible resolutions and improve the efficiency of the resolution.An illustrative example is given to verify the generalized semantic resolution algorithm based on linguistic 2-tuple propositional logic and demonstrate its effectiveness and feasibility.In order to make the language closer to the expression of human natural language,and more easily to be recognized by computers.This paper proposes a generalized lock resolution method based on linguistic 2-tuple first-order logic,by combining the lock resolution strategy and linguistic 2-tuple first-order logic.The method of transforming linguistic 2-tuple first-order logic formula into Skolem normal form is given and the generalized lock resolution method in linguistic 2-tuple first-order logic is studied.This paper proposes generalized lock resolution method based on linguistic 2-tuple first-order logic and an illustrative example is given to demonstrate its effectiveness.