55 citations · 118 across the 5 of their papers we have counts for
5 papers
Robot Motion Planning as Video Prediction: A Spatio-Temporal Neural Network-based Motion Planner
Xiao Zang, Miao Yin, Lingyi Huang +3
Neural network (NN)-based methods have emerged as an attractive approach for robot motion planning due to strong learning capabilities of NN models and their inherently high parall…
Hybrid intelligence for dynamic job-shop scheduling with deep reinforcement learning and attention mechanism
Yunhui Zeng, Zijun Liao, Yuanzhi Dai +3
The dynamic job-shop scheduling problem (DJSP) is a class of scheduling tasks that specifically consider the inherent uncertainties such as changing order requirements and possible…
Boosting Offline Reinforcement Learning with Residual Generative Modeling
Hua Wei, Deheng Ye, Zhao Liu +5
Offline reinforcement learning (RL) tries to learn the near-optimal policy with recorded offline experience without online exploration. Current offline RL research includes: 1) gen…
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.…
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…