dailyai.report

GRASP optimizes long-horizon trajectories by lifting them into virtual states for parallel processing. This gradient-based planner integrates stochasticity directly into the world model to prevent optimization collapse. Researchers at BAIR developed the system to make complex, multi-step planning computationally practical. It allows agents to navigate longer sequences without the typical exponential cost of sequential search.