Interaction Modeling with Multiplex Attention

@article{Sun2022InteractionMW,
  title={Interaction Modeling with Multiplex Attention},
  author={Fan-Yun Sun and Isaac Kauvar and Ruohan Zhang and Jiachen Li and Mykel J. Kochenderfer and Jiajun Wu and Nick Haber},
  journal={ArXiv},
  year={2022},
  volume={abs/2208.10660}
}
Modeling multi-agent systems requires understanding how agents interact. Such systems are often difficult to model because they can involve a variety of types of interactions that layer together to drive rich social behavioral dynamics. Here we introduce a method for accurately modeling multi-agent systems. We present Interaction Modeling with Multiplex Attention (IMMA), a forward prediction model that uses a multiplex latent graph to represent multiple independent types of interactions and… 
1 Citations

Learning Heterogeneous Interaction Strengths by Trajectory Prediction with Graph Neural Network

The RAIN model with the PA mechanism accurately infers continuous interaction strengths for simulated physical systems in an unsupervised manner, and successfully predicts trajectories from motion capture data with an interpretable interaction graph, demonstrating the virtue of modeling unknown dynamics with continuous weights.

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