Supervised Learning Achieves Human-Level Performance in MOBA Games: A Case Study of Honor of Kings
Deheng Ye
Guibin Chen
P. Zhao
Fuhao Qiu
Bo Yuan
Wen Zhang
Sheng Chen
Mingfei Sun
Xiaoqian Li
Siqin Li
Jing Liang
Zhenjie Lian
Bei Shi
Liang Wang
Tengfei Shi
Qiang Fu
Wei Yang
Lanxiao Huang

Abstract
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) games. Unlike prior attempts, we integrate the macro-strategy and the micromanagement of MOBA-game-playing into neural networks in a supervised and end-to-end manner. Tested on Honor of Kings, the most popular MOBA at present, our AI performs competitively at the level of High King players in standard 5v5 games.
View on arXivComments on this paper