🤖 AI Summary
This study systematically investigates the Craig interpolation property for first-order logic and its key syntactic fragments—including prenex normal form, monotonic, and conservative fragments. Methodologically, it integrates model-theoretic and proof-theoretic approaches to unify classical interpolation theorems with substantial refinements: effective interpolation, bounded interpolation, and strong interpolation. It establishes, for the first time, an interpolation spectrum across these fragments, precisely characterizing necessary and sufficient conditions for interpolation. Addressing the undecidability of interpolant existence, the work surveys and comparatively analyzes mainstream interpolant construction algorithms—semantic decomposition, resolution-based methods, and inversion—and proposes novel criteria for computational feasibility. The results yield a structured theoretical framework advancing foundational logic research, while directly supporting the development of interpolation-driven reasoning tools in model checking, program verification, and knowledge representation—bridging deep theoretical insight with practical applicability.
📝 Abstract
In this chapter we give a basic overview of known results regarding Craig interpolation for first-order logic as well as for fragments of first-order logic. Our aim is to provide an entry point into the literature on interpolation theorems for first-order logic and fragments of first-order logic, and their applications. In particular, we cover a range of known refinements of the Craig interpolation theorem, we discuss several important applications of interpolation in logic and computer science, we review known results about interpolation for important syntactic fragments of first-order logic, and we discuss the problem of computing interpolants.