4 papers
Relational program synthesis with numerical reasoning
Céline Hocquette, Andrew Cropper
Program synthesis approaches struggle to learn programs with numerical values. An especially difficult problem is learning continuous values over multiple examples, such as interva…
Learning programs with magic values
Céline Hocquette, Andrew Cropper
A magic value in a program is a constant symbol that is essential for the execution of the program but has no clear explanation for its choice. Learning programs with magic values…
Beneficial and Harmful Explanatory Machine Learning
Lun Ai, Stephen H. Muggleton, Céline Hocquette +2
Given the recent successes of Deep Learning in AI there has been increased interest in the role and need for explanations in machine learned theories. A distinct notion in this con…
Can Meta-Interpretive Learning outperform Deep Reinforcement Learning of Evaluable Game strategies?
Céline Hocquette, Stephen H. Muggleton
World-class human players have been outperformed in a number of complex two person games (Go, Chess, Checkers) by Deep Reinforcement Learning systems. However, owing to tractabilit…