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Sheng Chen

6 papers hereh-index 10627 citations13 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author4

Across the 5 of 6 papers where every author was matched, so the position is known.

fields
  • cs.AI5
  • cs.HC1
same name
  • Sheng Chen — 12 papers, h 47
  • Sheng Chen — 7 papers, h 6
  • Sheng Chen — 7 papers, h 3
  • Sheng Chen — 7 papers, h 4
  • Sheng Chen — 7 papers, h 3
  • Sheng Chen — 7 papers, h 12

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20182024
most citedSupervised Learning Achieves Human-Level Performance in MOBA Games: A Case Study of Honor of Kings

55 citations · 97 across the 3 of their papers we have counts for

collaborators
Showing 2020 · cs.AIShow all

3 papers · 2 filters

cs.AI2020★ 42 cited

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.…

cs.AI2020

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…

cs.AI2020★ 55 cited

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…

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