Solving Dynamic Graph Problems with Multi-Attention Deep Reinforcement Learning. (arXiv:2201.04895v1 [cs.LG])

Graph problems such as traveling salesman problem, or finding minimal Steiner
trees are widely studied and used in data engineering and computer science.
Typically, in real-world applications, the features of the graph tend to change
over time, thus, finding a solution to the problem becomes challenging. The
dynamic version of many graph problems are the key for a plethora of real-world
problems in transportation, telecommunication, and social networks. In recent
years, using deep learning techniques to find heuristic solutions for …

arxiv attention graph learning reinforcement learning