63 citations · 118 across the 6 of their papers we have counts for
6 papers
On Efficient Reinforcement Learning for Full-length Game of StarCraft II
Ruo-Ze Liu, Zhen-Jia Pang, Zhou-Yu Meng +3
StarCraft II (SC2) poses a grand challenge for reinforcement learning (RL), of which the main difficulties include huge state space, varying action space, and a long time horizon.…
An Introduction of mini-AlphaStar
Ruo-Ze Liu, Wenhai Wang, Yanjie Shen +3
StarCraft II (SC2) is a real-time strategy game in which players produce and control multiple units to fight against opponent's units. Due to its difficulties, such as huge state s…
Shape Robust Text Detection with Progressive Scale Expansion Network
Wenhai Wang, Enze Xie, Xiang Li +4
Scene text detection has witnessed rapid progress especially with the recent development of convolutional neural networks. However, there still exists two challenges which prevent…
Efficient Reinforcement Learning for StarCraft by Abstract Forward Models and Transfer Learning
Ruo-Ze Liu, Haifeng Guo, Xiaozhong Ji +5
Injecting human knowledge is an effective way to accelerate reinforcement learning (RL). However, these methods are underexplored. This paper presents our discovery that an abstrac…
On Reinforcement Learning for Full-length Game of StarCraft
Zhen-Jia Pang, Ruo-Ze Liu, Zhou-Yu Meng +3
StarCraft II poses a grand challenge for reinforcement learning. The main difficulties of it include huge state and action space and a long-time horizon. In this paper, we investig…
Shape Robust Text Detection with Progressive Scale Expansion Network
Xiang Li, Wenhai Wang, Wenbo Hou +3
The challenges of shape robust text detection lie in two aspects: 1) most existing quadrangular bounding box based detectors are difficult to locate texts with arbitrary shapes, wh…