GHQ: Grouped Hybrid Q Learning for Heterogeneous Cooperative Multi-agent Reinforcement Learning

no code implementations • 2 Mar 2023 • Xiaoyang Yu, Youfang Lin, Xiangsen Wang, Sheng Han, Kai Lv

We firstly define and describe the heterogeneous problems in SMAC.

Q-Learning reinforcement-learning +3

Conservative Distributional Reinforcement Learning with Safety Constraints

no code implementations • 18 Jan 2022 • Hengrui Zhang, Youfang Lin, Sheng Han, Shuo Wang, Kai Lv

Then, CDMPO uses a conservative value function loss to reduce the number of violations of constraints during the exploration process.

Distributional Reinforcement Learning reinforcement-learning +1

$l_1$-regularized Outlier Isolation and Regression

no code implementations • 1 Jun 2014 • Sheng Han, Suzhen Wang, Xinyu Wu

This paper proposed a new regression model called $l_1$-regularized outlier isolation and regression (LOIRE) and a fast algorithm based on block coordinate descent to solve this model.

regression