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Weixun Wang

18 papers hereh-index 211.7k citations55 works total

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

author position
  • first author4
  • middle author14

Across the 18 of 18 papers where every author was matched, so the position is known.

fields
  • cs.LG7
  • cs.AI6
  • cs.MA4
  • cs.DC1
same name
  • Weixun Wang — 27 papers, h 11
  • Weixun Wang — 2 papers, h 3

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
20182022
most citedLearning to Utilize Shaping Rewards: A New Approach of Reward Shaping

94 citations · 215 across the 18 of their papers we have counts for

collaborators
Showing cs.MAShow all

4 papers · 1 filter

cs.MA2022

Off-Beat Multi-Agent Reinforcement Learning

Wei Qiu, Weixun Wang, Rundong Wang +7

We investigate model-free multi-agent reinforcement learning (MARL) in environments where off-beat actions are prevalent, i.e., all actions have pre-set execution durations. During…

cs.MA2020★ 6 cited

An Efficient Transfer Learning Framework for Multiagent Reinforcement Learning

Tianpei Yang, Weixun Wang, Hongyao Tang +9

Transfer Learning has shown great potential to enhance single-agent Reinforcement Learning (RL) efficiency. Similarly, Multiagent RL (MARL) can also be accelerated if agents can sh…

cs.MA2019★ 12 cited

Independent Generative Adversarial Self-Imitation Learning in Cooperative Multiagent Systems

Xiaotian Hao, Weixun Wang, Jianye Hao +1

Many tasks in practice require the collaboration of multiple agents through reinforcement learning. In general, cooperative multiagent reinforcement learning algorithms can be clas…

cs.MA2019★ 12 cited

Action Semantics Network: Considering the Effects of Actions in Multiagent Systems

Weixun Wang, Tianpei Yang, Yong Liu +6

In multiagent systems (MASs), each agent makes individual decisions but all of them contribute globally to the system evolution. Learning in MASs is difficult since each agent's se…

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