Beyond Static Graph World Models: Learning Stochastic Latent Dynamics over Evolving Topologies
Graph-based world models have recently emerged as a means of learning transitions over relational state representations. However, existing approaches are largely limited to fixed-topology graphs or deterministic, fully observable environments. We propose the Graph Dynamics Model (GDM), a world model for graph-structure...