SLDR-DL: A Framework for SLD-Resolution with Deep Learning
Artificial Intelligence
2017-05-08 v1 Machine Learning
Logic in Computer Science
Abstract
This paper introduces an SLD-resolution technique based on deep learning. This technique enables neural networks to learn from old and successful resolution processes and to use learnt experiences to guide new resolution processes. An implementation of this technique is named SLDR-DL. It includes a Prolog library of deep feedforward neural networks and some essential functions of resolution. In the SLDR-DL framework, users can define logical rules in the form of definite clauses and teach neural networks to use the rules in reasoning processes.
Cite
@article{arxiv.1705.02210,
title = {SLDR-DL: A Framework for SLD-Resolution with Deep Learning},
author = {Cheng-Hao Cai},
journal= {arXiv preprint arXiv:1705.02210},
year = {2017}
}
Comments
12 pages, 5 figures