  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.
