1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.LG2022★ 1 cited
Generative Adversarial Exploration for Reinforcement Learning
Weijun Hong, Menghui Zhu, Minghuan Liu +4
Exploration is crucial for training the optimal reinforcement learning (RL) policy, where the key is to discriminate whether a state visiting is novel. Most previous work focuses o…
cs.AI2021
MapGo: Model-Assisted Policy Optimization for Goal-Oriented Tasks
Menghui Zhu, Minghuan Liu, Jian Shen +7
In Goal-oriented Reinforcement learning, relabeling the raw goals in past experience to provide agents with hindsight ability is a major solution to the reward sparsity problem. In…
cs.AI2020
Which Heroes to Pick? Learning to Draft in MOBA Games with Neural Networks and Tree Search
Sheng Chen, Menghui Zhu, Deheng Ye +3
Hero drafting is essential in MOBA game playing as it builds the team of each side and directly affects the match outcome. State-of-the-art drafting methods fail to consider: 1) dr…