Learning programs by learning from failures

We describe an inductive logic programming (ILP) approach called learning from failures . In this approach, an ILP system (the learner) decomposes the learning problem into three separate stages: generate , test , and constrain . In the generate stage, the learner generates a hypothesis (a logic pro...

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Bibliographic Details
Published in:	Machine learning Vol. 110; no. 4; pp. 801 - 856
Main Authors:	Cropper, Andrew, Morel, Rolf
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.04.2021 Springer Nature B.V
Subjects:	Artificial Intelligence Computer Science Control Declarative programming Domains Hypotheses Learning programs Logic programming Logic programs Machine Learning Mathematical programming Mechatronics Natural Language Processing (NLP) Prolog Robotics Simulation and Modeling Special issue on Learning and Reasoning Inductive logic programming Program synthesis Program induction
ISSN:	0885-6125, 1573-0565
Online Access:	Get full text
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