探索偏差:特别是在EGNN(Equivariant Graph Neural Networks)中,由于其特定的等变计算性质,在学习的早期阶段会导致探索偏差,从而影响智能体发现最优策略的能力。 为了解决这些问题,论文提出了一种新的网络结构——探索增强的等变图神经网络(E2GN2),它通过以下方式来提高样本效率和泛化能力: 引入等变图神经网络(EGNN),...
[3.6]Chapter 22 | Graph Neural Networks in Program Analysis [3.7]PLUR: A Unifying, Graph-Based View of Program Learning, Understanding, and Repair (neurips.cc) [3.8]The Tolman-Eichenbaum Machine: Unifying Space and Relational Memory through Generalization in the Hippocampal Formation: Cell...
based on the comparisons with previous work:(1)we realize feasible and dynamic adjacent information fusion using GraphSAGE(i.e.,Graph SAmple and aggreGatE),which is the first time this method has been used to deal with the cooperative planning problem,and(2)a task-oriented sampling method is ...
Focusing on the problems, we propose a leader-follower flocking algorithm based on a novel reinforcement learning (RL) model. We construct a homogeneous graph neural network (GNN) based multi-agent deep deterministic policy gradient (herein HGNN-MADDPG) algorithm model for multi-agent flocking ...
In this study, a novel graph-embedding technique based on a graph neural network (GNN) is proposed to identify the topology in the motion of a unmanned aerial vehicles (UAV) swarm and quickly obtain local information around each agent. We also propose a model reference reinforcement learning me...
Not only that, I can also recommend suitable practice questions based on your learning progress to help you consolidate knowledge and improve learning efficiency. Additionally, I will use LaTeX format as much as possible to present the solution process and formulas....
[15]I. Nikoloska, O. Simeone. Modular meta-learning for power control via random edge graph neural networks[J]. IEEE Transactions on Wireless Communications, 2023,22(1): 457-470. [16]Y. Shen, Y. Shi, J. Zhang, et al. Graph neural networks for scalable radio resource management: Archi...
In this paper, we address the problem of distributed Bayesian estimation in networks of agents over a given undirected graph. The agents observe data repre... Y Wang,Petar M. Djuri - 《IEEE Transactions on Signal Processing》 被引量: 1发表: 2016年 Fast Simulation-Based Bayesian Estimation ...
4. All in One: Multi-task Prompting for Graph Neural Networks 论文研究了图神经网络 (Graph Neural Networks,GNNs) 的 prompting 问题,以解决预处理和微调方法在处理各种图任务时存在的不兼容性问题。虽然预处理和微调方法可以缓解缺乏图形注释的问题,但是节点级别、边级别和图级别任务的多样化使得预处理方法往往无...
decentralized policies that operate based on local observations and messages received from network neighbors Graph Neural Networks a scalable framework that can naturally process information within the coordination graph in an expressive manner. Graph neural networks (GNNs) are a fundamental tool for handli...