Abstract
The last three decades has seen the development of Computational Logic techniques within Artificial Intelligence. This has led to the development of the subject of Logic Programming (LP), which can be viewed as a key part of Logic-Based Artificial Intelligence. The subtopic of LP concerned with Machine Learning is known as “Inductive Logic Programming” (ILP), which again can be broadened to Logic-Based Machine Learning by dropping Horn clause restrictions. ILP has its roots in the ground-breaking research of Gordon Plotkin and Ehud Shapiro. This paper provides a brief survey of the state of ILP applications, theory and techniques.
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Muggleton, S., Marginean, F. (2000). Logic-Based Machine Learning. In: Minker, J. (eds) Logic-Based Artificial Intelligence. The Springer International Series in Engineering and Computer Science, vol 597. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-1567-8_14
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DOI: https://doi.org/10.1007/978-1-4615-1567-8_14
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