3 citations · 5 across the 4 of their papers we have counts for
4 papers
A Deep Reinforcement Learning Strategy for UAV Autonomous Landing on a Platform
Z. Jiang, G. Song
With the development of industry, drones are appearing in various field. In recent years, deep reinforcement learning has made impressive gains in games, and we are committed to ap…
Entropy Enhanced Multi-Agent Coordination Based on Hierarchical Graph Learning for Continuous Action Space
Yining Chen, Ke Wang, Guanghua Song +1
In most existing studies on large-scale multi-agent coordination, the control methods aim to learn discrete policies for agents with finite choices. They rarely consider selecting…
Soft Hierarchical Graph Recurrent Networks for Many-Agent Partially Observable Environments
Zhenhui Ye, Xiaohong Jiang, Guanghua Song +1
The recent progress in multi-agent deep reinforcement learning(MADRL) makes it more practical in real-world tasks, but its relatively poor scalability and the partially observable…
Experience Augmentation: Boosting and Accelerating Off-Policy Multi-Agent Reinforcement Learning
Zhenhui Ye, Yining Chen, Guanghua Song +2
Exploration of the high-dimensional state action space is one of the biggest challenges in Reinforcement Learning (RL), especially in multi-agent domain. We present a novel techniq…