Least Generalizations and Greatest Specializations of Sets of Clauses
S. H. Nienhuys-Cheng, R. deWolf
Abstract
The main operations in Inductive Logic Programming (ILP) are generalization and specialization, which only make sense in a generality order. In ILP, the three most important generality orders are subsumption, implication and implication relative to background knowledge. The two languages used most often are languages of clauses and languages of only Horn clauses. This gives a total of six different ordered languages. In this paper, we give a systematic treatment of the existence or non-existence of least generalizations and greatest specializations of finite sets of clauses in each of these six ordered sets. We survey results already obtained by others and also contribute some answers of our own. Our main new results are, firstly, the existence of a computable least generalization under implication of every finite set of clauses containing at least one non-tautologous function-free clause (among other, not necessarily function-free clauses). Secondly, we show that such a least generalization need not exist under relative implication, not even if both the set that is to be generalized and the background knowledge are function-free. Thirdly, we give a complete discussion of existence and non-existence of greatest specializations in each of the six ordered languages.
Create a lesson
Related papers
WikiSkill: Compiling Agent Experience into Persistent Knowledge for Skill Evolution
Liyan Tang, Cyrus Rashtchian, Chun-Sung Ferng et al.
Mechanistic Reaction Prediction via Discrete Flow Matching on Graph-Structured Electron Occupation
Nguyen Xuan-Vu, Octavian Susanu, Daniel Armstrong et al.
Learning a Continuous Sepsis Severity Score Without Hour-by-Hour Supervision: A Two-Site Retrospective Study
Kevin Zhu, Ryan Zhang, Baraa Abed et al.
CorporateBench: Large-Scale Q&A Benchmarking with Temporal Knowledge Bases
Sil Hamilton, Albert Yu Sun, Oscar J. Romero et al.
Sophistication in GenAI Use: Field Evidence from a Large Firm
Nicholas J. Hallman, Zachary T. Kowaleski, Anu Puvvada et al.
Not All Eval-Awareness Is Equal: Capabilities Framing Predicts Compliance
Allison Zhuang, Santiago Aranguri