55 citations · 97 across the 2 of their papers we have counts for
4 papers · 1 filter
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…
Towards Playing Full MOBA Games with Deep Reinforcement Learning
Deheng Ye, Guibin Chen, Wen Zhang +15
MOBA games, e.g., Honor of Kings, League of Legends, and Dota 2, pose grand challenges to AI systems such as multi-agent, enormous state-action space, complex action control, etc.…
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…
Supervised Learning Achieves Human-Level Performance in MOBA Games: A Case Study of Honor of Kings
Deheng Ye, Guibin Chen, Peilin Zhao +15
We present JueWu-SL, the first supervised-learning-based artificial intelligence (AI) program that achieves human-level performance in playing multiplayer online battle arena (MOBA…