4.7 Article

Generating contrastive explanations for inductive logic programming based on a near miss approach

Related references

Note: Only part of the references are listed.
Article Computer Science, Artificial Intelligence

Beneficial and harmful explanatory machine learning

Lun Ai et al.

Summary: This paper explores the explanatory effects of machine learned theories in human learning, proposing a framework to identify the harmfulness of machine explanations based on the cognitive window concept. Empirical evidence shows that human performance is significantly improved when aided by a symbolic machine learned theory that satisfies the cognitive window, while performance declines when aided by a theory that fails to satisfy the window.

MACHINE LEARNING (2021)

Article Computer Science, Artificial Intelligence

Explanation in artificial intelligence: Insights from the social sciences

Tim Miller

ARTIFICIAL INTELLIGENCE (2019)

Article Computer Science, Artificial Intelligence

The teaching size: computable teachers and learners for universal languages

Jan Arne Telle et al.

MACHINE LEARNING (2019)

Proceedings Paper Computer Science, Artificial Intelligence

Efficient Data Representation by Selecting Prototypes with Importance Weights

Karthik S. Gurumoorthy et al.

2019 19TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING (ICDM 2019) (2019)

Article Computer Science, Artificial Intelligence

Please delete that! Why should I?: Explaining learned irrelevance classifications of digital objects

Michael Siebers et al.

KUNSTLICHE INTELLIGENZ (2019)

Article Computer Science, Artificial Intelligence

Ultra-Strong Machine Learning: comprehensibility of programs learned with ILP

Stephen H. Muggleton et al.

MACHINE LEARNING (2018)

Article Computer Science, Information Systems

Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)

Amina Adadi et al.

IEEE ACCESS (2018)

Proceedings Paper Computer Science, Software Engineering

Believe it or not: Designing a Human-AI Partnership for Mixed-Initiative Fact-Checking

An T. Nguyen et al.

UIST 2018: PROCEEDINGS OF THE 31ST ANNUAL ACM SYMPOSIUM ON USER INTERFACE SOFTWARE AND TECHNOLOGY (2018)

Article Multidisciplinary Sciences

Hybrid computing using a neural network with dynamic external memory

Alex Graves et al.

NATURE (2016)

Article Statistics & Probability

PROTOTYPE SELECTION FOR INTERPRETABLE CLASSIFICATION

Jacob Bien et al.

ANNALS OF APPLIED STATISTICS (2011)

Article Psychology, Educational

Learning and transfer: A general role for analogical encoding

D Gentner et al.

JOURNAL OF EDUCATIONAL PSYCHOLOGY (2003)