… for training various decision-making modes with emphasis on decision-making styles and
… via graph model to better represent the interaction between vehicles, and adopt the graph …

… the decision-making process, this paper proposes a generalized single-vehicle-based graph
neural network reinforcement … The SGRL algorithm introduces graph convolution into the …

… To this end, this paper presents a novel EVCN decisionmaking platform based on graph
reinforcement learning (GRL) composed of GCN and DRL. From the perspective of ‘Vehicle-…

… , the fusion of graph technology, such as graph representation and graph neural network (…
This type of method can be termed as a graph reinforcement learning (GRL)-based method. …

… cooperative decisions generation. To tackle these difficulties, this research proposes a
framework to enable different Graph Reinforcement Learning (GRL) methods for decision-making…

… decision making research has gradually embraced the issue of learning, coming to inquire
not only how decisions … stimulus order determined by the graph in Figure 3c. Each node in the …

… methods are more appropriate for our uncertainty-based decision making scenario. As we
present experiments for graph data in the Section V, the action space in a complexity relation …

… Graph Attention Reinforcement Learning (EGARL) framework that aims to make rational
driving decisions … interactive information; an Edge-enhanced Graph Attention Network (E-GAT) …

… realize different Graph Reinforcement Learning (GRL) methods for better decision-making in
… are modeled by graph representation, and features are extracted via Graph Neural Network …

… of Graph Reinforcement Learning (GRL) ranging from January 2017 to November 2022 in
Fig. 1 to prove the fusion of graph mining methods with RL for graph… and decision making, and …