2.2 Reinforcement Learning in Graph 强化学习(RL)取得了显著成功解决具有挑战性的问题。 RL在图卷积网络中的工作有: 【1】Kien Do, Truyen Tran, and Svetha Venkatesh. 2019. Graph transformation policy network for chemical reaction prediction. In Proceedings ofthe 25th ACMSIGKDD International Conference o...
Graph neural networks (GNNs) have recently emerged as revolutionary technologies for machine learning tasks on graphs. In GNNs, the graph structure is generally incorporated with node representation via the message passing scheme, making the explanation much more challenging. Given a...
Adversarial Machine Learning has emerged as a substantial subfield of Computer Science due to a lack of robustness in the models we train along with crowdsourcing practices that enable attackers to tamper with data. In the last two years, interest has surged in adversarial attacks on graphs yet ...
As an answer to these limitations, this paper introduces Householder reflection as the basic mathematical tool and presents the design of two linear transformations based on it to model relations in knowledge graphs. The two linear transformations are: (1) Ho...
【RLChina论文研讨会】第93期 耿子介 Reinforcement Learning with Tree Search for Fast Macro Pl, 视频播放量 384、弹幕量 0、点赞数 8、投硬币枚数 1、收藏人数 10、转发人数 0, 视频作者 RLChina强化学习社区, 作者简介 ,相关视频:【RLChina论文研讨会】第95期 庄子文
ReLMoGen: Integrating Motion Generation in Reinforcement Learning for Mobile Manipulation 许多强化学习 (RL) 方法使用联合控制信号(位置、速度、扭矩)作为连续控制任务的动作空间。我们建议以运动生成器(运动规划器和轨迹执行器的组合)的子目标的形式将动作空间提升到更高的水平。我们认为,通过提升动作空间和利用基于...
Reinforcement learning on graphs: A survey recent years, and there has been some pioneering work employing the research-rich Reinforcement Learning (RL) techniques to address graph data mining tasks... N Mingshuo,C Dongming,W Dongqi 被引量: 0发表: 2022年 Deep reinforcement learning in computer...
We propose an algorithm based on reinforcement learning for solving NP-hard problems on graphs. We combine Graph Isomorphism Networks and the Monte-Carlo Tree Search, which was originally used for game searches, for solving combinatorial optimization on graphs. Similarly to AlphaGo Zero, our method ...
Zero-Shot Reinforcement Learning on Graphs for Autonomous Exploration We are excited that our paper "Zero-Shot Reinforcement Learning on Graphs for Autonomous Exploration Under Uncertainty" has been accepted for presentation at ICRA 2021. In the video above, which assumes a lidar-equipped mobile robot...
,butnotovernew topologies.Thereasonbehindthisimportantlimitationis thatexistingDRLnetworkingsolutionsusestandardneural networks(e.g., ullyconnected),whichareunabletolearn graph-structuredin ormation.Inthispaperweproposeto useGraphNeuralNetworks(GNN)incombinationwithDRL. GNNhavebeenrecentlyproposedtomodelgraphs,...