25 citations · 30 across the 3 of their papers we have counts for
3 papers
cs.AI2022★ 4 cited
Multi-Agent Policy Transfer via Task Relationship Modeling
Rongjun Qin, Feng Chen, Tonghan Wang +5
Team adaptation to new cooperative tasks is a hallmark of human intelligence, which has yet to be fully realized in learning agents. Previous work on multi-agent transfer learning…
cs.LG2021★ 25 cited
NeoRL: A Near Real-World Benchmark for Offline Reinforcement Learning
Rongjun Qin, Songyi Gao, Xingyuan Zhang +5
Offline reinforcement learning (RL) aims at learning a good policy from a batch of collected data, without extra interactions with the environment during training. However, current…
cs.LG2019★ 1 cited
Improving Fictitious Play Reinforcement Learning with Expanding Models
Rong-Jun Qin, Jing-Cheng Pang, Yang Yu
Fictitious play with reinforcement learning is a general and effective framework for zero-sum games. However, using the current deep neural network models, the implementation of fi…