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Neural Online Graph Exploration
[article]
2021
arXiv
pre-print
Can we learn how to explore unknown spaces efficiently? To answer this question, we study the problem of Online Graph Exploration, the online version of the Traveling Salesperson Problem. We reformulate graph exploration as a reinforcement learning problem and apply Direct Future Prediction (Dosovitskiy and Koltun, 2017) to solve it. As the graph is discovered online, the corresponding Markov Decision Process entails a dynamic state space, namely the observable graph and a dynamic action space,
arXiv:2012.03345v2
fatcat:7czvjtzgrndz3oses7sqfq2yta