Planning Under Observation Mismatch for Traffic Signal Control via Adaptive Modular World Models

ArXi:2501.02548v2 Announce Type: replace Deploying learned decision-making systems often requires transferring to new sites where the sensing pipeline differs. In such cases, observations can change in semantics and dimensionality even when action primitives and objectives remain comparable. In this work, we study transferable model-based planning under this observation mismatch, which remains challenging for existing learning-based approaches.