Causal Graph ODE: Continuous Treatment Effect Modeling in Multi-agent Dynamical Systems

arXiv:2403.00178v1 Announce Type: new
Abstract: Real-world multi-agent systems are often dynamic and continuous, where the agents co-evolve and undergo changes in their trajectories and interactions over time. For example, the COVID-19 transmission in the U.S. can be viewed as a multi-agent system, where states act as agents and daily population movements between them are interactions. Estimating the counterfactual outcomes in such systems enables accurate future predictions and effective decision-making, such as formulating COVID-19 policies. However, existing methods fail to model …

abstract act agent agents arxiv continuous covid covid-19 cs.ai cs.lg daily dynamic example graph interactions modeling multi-agent systems treatment type world