dailyai.report

The GRASP planner lifts trajectories into virtual states to parallelize optimization across time. This approach allows gradient-based planning to function over longer horizons without the usual computational collapse. Researchers at BAIR integrated stochasticity directly into the process. It provides a more efficient path for training autonomous agents in complex environments.