  This paper presents preliminary work on using deep neural networks to guide
general-purpose heuristic algorithms for performing utilitarian combinatorial
assignment. In more detail, we use deep learning in an attempt to produce
heuristics that can be used together with e.g., search algorithms to generate
feasible solutions of higher quality more quickly. Our results indicate that
our approach could be a promising future method for constructing such
heuristics.
