Beneficial and harmful explanatory machine learning

DOI10.1007/s10994-020-05941-0OpenAlexW3139019272MaRDI QIDQ2051274

Mark Gromowski, Lun Ai, Ute Schmid, Céline Hocquette, Stephen H. Muggleton

Publication date: 24 November 2021

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2009.06410

zbMATH Keywords

inductive logic programmingcomprehensibilityultra-strong machine learningexplainable AI

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (3)

Inductive logic programming at 30 ⋮ Generating contrastive explanations for inductive logic programming based on a near miss approach ⋮ Simplification of genetic programs: a literature survey

Uses Software

• GitHub
• Metagol
• Metaopt

Cites Work

• Unnamed Item
• Ultra-strong machine learning: comprehensibility of programs learned with ILP
• On the complexity of teaching
• Meta-interpretive learning: application to grammatical inference
• The teaching size: computable teachers and learners for universal languages
• Explanation in artificial intelligence: insights from the social sciences
• Learning efficient logic programs
• Inductive logic programming
• Relational reinforcement learning

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