Goal-Guided Graph Attention Network with Interactive State Refinement for Multi-Agent Trajectory Prediction.
Jianghang WuSenyao QiaoHaocheng LiBoyu SunFei GaoHongyu HuRui ZhaoPublished in: Sensors (2024)
Keyphrases
- multi agent
- prediction accuracy
- cooperative
- fully connected
- state information
- wireless sensor networks
- video sequences
- dynamic networks
- path length
- spanning tree
- graph theory
- state space
- sparsely connected
- bipartite graph
- computer networks
- refinement operators
- location prediction
- power law
- communication networks
- random walk
- prediction algorithm
- elman network
- leader follower
- degree distribution
- maximum flow
- artificial neural networks
- random graphs
- network structure
- graphical representation
- graph theoretic
- complex networks
- link prediction
- graph matching