Towards Utilitarian Combinatorial Assignment with Deep Neural Networks and Heuristic Algorithms
Artificial Intelligence
2021-07-02 v1
Abstract
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.
Cite
@article{arxiv.2107.00317,
title = {Towards Utilitarian Combinatorial Assignment with Deep Neural Networks and Heuristic Algorithms},
author = {Fredrik Präntare and Mattias Tiger and David Bergström and Herman Appelgren and Fredrik Heintz},
journal= {arXiv preprint arXiv:2107.00317},
year = {2021}
}
Comments
7 pages, 4 figures, presented at the ECAI 2020 TAILOR workshop