Anti-unification and Generalization: A Survey

TL;DR

This survey comprehensively reviews anti-unification, a key operation in AI for generalization, highlighting its theoretical foundations, applications, and providing a framework for future research.

Contribution

It is the first systematic survey of anti-unification research, offering a unified framework and categorization of existing and potential future work.

Findings

Provides a comprehensive overview of anti-unification concepts.

Introduces a general framework for categorizing AU research.

Identifies gaps and directions for future AU research.

Abstract

Anti-unification (AU) is a fundamental operation for generalization computation used for inductive inference. It is the dual operation to unification, an operation at the foundation of automated theorem proving. Interest in AU from the AI and related communities is growing, but without a systematic study of the concept nor surveys of existing work, investigations often resort to developing application-specific methods that existing approaches may cover. We provide the first survey of AU research and its applications and a general framework for categorizing existing and future developments.