Prismatic World Model: Learning Compositional Dynamics for Planning in Hybrid Systems

This paper introduces the Prismatic World Model (PRISM-WM), a structured architecture to decompose complex hybrid dynamics into composable primitives for robust planning in robotic domains. By accurately modeling sharp mode transitions, PRISM-WM significantly reduces rollout drift, providing a high-fidelity substrate for trajectory optimization algorithms.