Inconsistency and the dilemma of intuitionistic research in generative syntax

The paper is a contribution to the current debate on linguistic data and evidence. It raises two questions: (a) What kinds of inconsistency do emerge in generative syntax? (b) How are these kinds of inconsistency to be evaluated with respect to the workability of the syntactic theory at issue? As a first step, a system of paraconsistent logic is introduced which distinguishes between weak and strong inconsistency. While weak inconsistency is harmless, strong inconsistency is destructive. Second, a case study demonstrates that in generative syntax weak inconsistency may be a useful tool of problem solving. Third, two further case studies show that intuition as a data source triggers the emergence of strong inconsistency in generative syntax. Finally, this results in a methodological dilemma with far-reaching consequences

Zero-one laws with respect to models of provability logic and two Grzegorczyk logics

It has been shown in the late 1960s that each formula of first-order logic without constants and function symbols obeys a zero-one law: As the number of elements of finite models increases, every formula holds either in almost all or in almost no models of that size. Therefore, many properties of models, such as having an even number of elements, cannot be expressed in the language of first-order logic. Halpern and Kapron proved zero-one laws for classes of models corresponding to the modal logics K, T, S4, and S5 and for frames corresponding to S4 and S5. In this paper, we prove zero-one laws for provability logic and its two siblings Grzegorczyk logic and weak Grzegorczyk logic, with respect to model validity. Moreover, we axiomatize validity in almost all relevant finite models, leading to three different axiom systems

Multi-Criteria Assignment Techniques in Multi- Dimensional Neutrosophic Soft Set Theory

In this paper, we have introduced a new concept of multi-dimensional neutrosophic soft sets together with various operations, properties and theorems on them. Then we have proposed an algorithm named 2-DNS based on our proposed two-dimensional neutrosophic soft set for solving neutrosophic multi-criteria assignment problems with multiple decision makers