Is Centralized Training with Decentralized Execution Framework Centralized Enough for MARL?

1 code implementation • 27 May 2023 • Yihe Zhou, Shunyu Liu, Yunpeng Qing, KaiXuan Chen, Tongya Zheng, Yanhao Huang, Jie Song, Mingli Song

Despite the encouraging results achieved, CTDE makes an independence assumption on agent policies, which limits agents to adopt global cooperative information from each other during centralized training.

Multi-agent Reinforcement Learning reinforcement-learning +2

An Interactive Insight Identification and Annotation Framework for Power Grid Pixel Maps using DenseU-Hierarchical VAE

no code implementations • 22 May 2019 • Tianye Zhang, Haozhe Feng, Zexian Chen, Can Wang, Yanhao Huang, Yong Tang, Wei Chen

Insights in power grid pixel maps (PGPMs) refer to important facility operating states and unexpected changes in the power grid.

Deep-learning Based Modeling of Fault Detachment Stability for Power Grid

no code implementations • 17 May 2018 • Haotian Cui, Xianggen Liu, Yanhao Huang

The so-called "fail-delay cut-off" refers to the occurrence of N-1 backup protection action on the backbone network of the system, resulting in longer time for the removal of the fault.