Research6h ago
GRASP Enables Long-Horizon Planning for World Models
The GRASP planner optimizes long-horizon trajectories by lifting them into virtual states for parallel processing. This approach reduces the computational burden of gradient-based planning in learned dynamics. Researchers at BAIR integrated stochasticity directly into the process to improve robustness. The method allows agents to plan more effectively over extended timeframes.