Supervised Learning Achieves Human-Level Performance in MOBA Games: A
Case Study of Honor of Kings
IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2020
Liang Wang
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.
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