38 citations · 76 across the 8 of their papers we have counts for
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cs.LG2021★ 16 cited
RMIX: Learning Risk-Sensitive Policies for Cooperative Reinforcement Learning Agents
Wei Qiu, Xinrun Wang, Runsheng Yu +5
Current value-based multi-agent reinforcement learning methods optimize individual Q values to guide individuals' behaviours via centralized training with decentralized execution (…
cs.LG2021★ 2 cited
DO-GAN: A Double Oracle Framework for Generative Adversarial Networks
Aye Phyu Phyu Aung, Xinrun Wang, Runsheng Yu +3
In this paper, we propose a new approach to train Generative Adversarial Networks (GANs) where we deploy a double-oracle framework using the generator and discriminator oracles. GA…
cs.LG2020★ 9 cited
Learning to Collaborate in Multi-Module Recommendation via Multi-Agent Reinforcement Learning without Communication
Xu He, Bo An, Yanghua Li +6
With the rise of online e-commerce platforms, more and more customers prefer to shop online. To sell more products, online platforms introduce various modules to recommend items wi…