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...
2024, IEEE Transactions on Neural Networks and Learning Systems Recent developments in machine and human intelligence 2023, Recent Developments in Machine and Human Intelligence Reinforcement Learning on Graphs: A Survey 2023, IEEE Transactions on Emerging Topics in Computational Intelligence View all citing...
proposed to model and operate on graphs with the aim o achieving relational reasoning and combinatorial generaliza- tion. In other words, GNNs acilitate the learning o relations between entities in a graph and the rules or composing them. ...
Knowledge graphs (KGs) have been widely used to improve recommendation accuracy. The multi-hop paths on KGs also enable recommendation reasoning, which is considered a crystal type of explainability. In this paper, we propose a reinforcement learning framework for...
d. A tutorial on Bayesian optimization of expensive cost functions, with application to active user modeling and hierarchical reinforcement learning. Preprint at https://arxiv.org/abs//1012.2599 (2010). Cao, N. D. & Kipf, T. MolGAN: an implicit generative model for small molecular graphs. ...
(GCN, GAT, etc.) are used to learn representations of nodes in heterophilous graphs, node representations are easily misled by heterophilous neighbors, which could lead to poor representation learning. To address this problem, researchers have pr...
Cui, W.W. Zhu Deep learning on graphs: a survey IEEE Trans Knowl Data Eng, 34 (1) (2022), pp. 249-270 CrossrefView in ScopusGoogle Scholar 12 B. Gaudet, R. Furfaro, R. Linares Reinforcement learning for angle-only intercept guidance of maneuvering targets Aerosp Sci Technol, 99 (C...
Liu Z, Wan L, Sui X, et al. Deep Hierarchical Communication Graph in Multi-Agent Reinforcement Learning[C]//International Joint Conference on Artificial Intelligence (IJCAI). 2023, 35: 208-216. ijca…
Decentralized Multiagent Reinforcement Learning for Efficient Robotic Control by Coordination GraphsRLRobotic controlMultiagent learningCGReinforcement learning is widely used to learn complex behaviors for robotics. However, due to the high-dimensional state/action spaces, reinforcement learning usually suffers...
Learning Combinatorial Optimization Algorithms over Graphs Abstract 解决NP-hard问题通常需要大量的专业知识和反复试验, learn algorithm to automate this challenging, tedious process. learn heuristic algorithm利用结构特征解决问题. (sa... Neural Architecture Search with Reinforcement Learning论文总结 ...