Learning MDL logic programs from noisy data

08/18/2023
by   Céline Hocquette, et al.
0

Many inductive logic programming approaches struggle to learn programs from noisy data. To overcome this limitation, we introduce an approach that learns minimal description length programs from noisy data, including recursive programs. Our experiments on several domains, including drug design, game playing, and program synthesis, show that our approach can outperform existing approaches in terms of predictive accuracies and scale to moderate amounts of noise.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset