Skip to main content

3 Result(s)

within ShuHong Liu Remove this filter Computer Science Remove this filter

and

  1. No Access

    Chapter and Conference Paper

    MRRC: Multi-agent Reinforcement Learning with Rectification Capability in Cooperative Tasks

    Motivated by the centralised training with decentralised execution (CTDE) paradigm, multi-agent reinforcement learning (MARL) algorithms have made significant strides in addressing cooperative tasks. However, ...

    Sheng Yu, Wei Zhu, Shuhong Liu, Zhengwen Gong, Haoran Chen in Neural Information Processing (2024)

  2. No Access

    Chapter and Conference Paper

    PRACM: Predictive Rewards for Actor-Critic with Mixing Function in Multi-Agent Reinforcement Learning

    Inspired by the centralised training with decentralised execution (CTDE) paradigm, the field of multi-agent reinforcement learning (MARL) has made significant progress in tackling cooperative problems with dis...

    Sheng Yu, Bo Liu, Wei Zhu, Shuhong Liu in Knowledge Science, Engineering and Management (2023)

  3. No Access

    Article

    Simulations of unsteady cavitating turbulent flow in a Francis turbine using the RANS method and the improved mixture model of two-phase flows

    This paper reports the simulation results for the unsteady cavitating turbulent flow in a Francis turbine using the mixture model for cavity–liquid two-phase flows. The RNG k–ε turbulence model is employed in the...

    Yulin Wu, Shuhong Liu, Hua-Shu Dou, Liang Zhang in Engineering with Computers (2011)