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Shuai Han

4 papers here

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

author position
  • first author2
  • middle author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG4
same name
  • Shuai Han — 4 papers, h 23
  • Shuai Han — 2 papers
  • Shuai Han — 1 paper, h 2
  • Shuai Han — 1 paper
  • Shuai Han — 1 paper, h 1

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

most citedNROWAN-DQN: A Stable Noisy Network with Noise Reduction and Online Weight Adjustment for Exploration

4 citations · 11 across the 4 of their papers we have counts for

collaborators

4 papers

cs.LG2020★ 3 cited

Proximal Policy Optimization via Enhanced Exploration Efficiency

Junwei Zhang, Zhenghao Zhang, Shuai Han +1

Proximal policy optimization (PPO) algorithm is a deep reinforcement learning algorithm with outstanding performance, especially in continuous control tasks. But the performance of…

cs.LG2020★ 1 cited

Regularly Updated Deterministic Policy Gradient Algorithm

Shuai Han, Wenbo Zhou, Shuai Lü +1

Deep Deterministic Policy Gradient (DDPG) algorithm is one of the most well-known reinforcement learning methods. However, this method is inefficient and unstable in practical appl…

cs.LG2020★ 4 cited

NROWAN-DQN: A Stable Noisy Network with Noise Reduction and Online Weight Adjustment for Exploration

Shuai Han, Wenbo Zhou, Jing Liu +1

Deep reinforcement learning has been applied more and more widely nowadays, especially in various complex control tasks. Effective exploration for noisy networks is one of the most…

cs.LG2019★ 3 cited

Recruitment-imitation Mechanism for Evolutionary Reinforcement Learning

Shuai Lü, Shuai Han, Wenbo Zhou +1

Reinforcement learning, evolutionary algorithms and imitation learning are three principal methods to deal with continuous control tasks. Reinforcement learning is sample efficient…

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