dailyai.report

The GRASP planner lifts trajectories into virtual states to parallelize optimization across time. This approach allows learned dynamics models to plan over longer horizons without the typical computational collapse. Researchers at BAIR used stochasticity to improve search efficiency. Practitioners can now apply gradient-based planning to more complex, extended temporal tasks.