Research2d ago
GRASP Enables Long-Horizon World Model Planning
The GRASP planner optimizes trajectories by lifting them into virtual states to allow parallelization across time. This approach solves the computational bottlenecks typical of gradient-based planning in learned dynamics. By adding stochasticity directly to the process, it improves stability. Practitioners can now execute longer-horizon planning without the usual exponential cost.