8 citations · 16 across the 4 of their papers we have counts for
4 papers · 1 filter
Improving Generalization of Deep Reinforcement Learning-based TSP Solvers
Wenbin Ouyang, Yisen Wang, Shaochen Han +2
Recent work applying deep reinforcement learning (DRL) to solve traveling salesman problems (TSP) has shown that DRL-based solvers can be fast and competitive with TSP heuristics f…
Safe Distributional Reinforcement Learning
Jianyi Zhang, Paul Weng
Safety in reinforcement learning (RL) is a key property in both training and execution in many domains such as autonomous driving or finance. In this paper, we formalize it with a…
Analytics and Machine Learning in Vehicle Routing Research
Ruibin Bai, Xinan Chen, Zhi-Long Chen +13
The Vehicle Routing Problem (VRP) is one of the most intensively studied combinatorial optimisation problems for which numerous models and algorithms have been proposed. To tackle…
Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning
Matthieu Zimmer, Claire Glanois, Umer Siddique +1
We consider the problem of learning fair policies in (deep) cooperative multi-agent reinforcement learning (MARL). We formalize it in a principled way as the problem of optimizing…