dailyai.report

The GRASP planner lifts trajectories into virtual states to parallelize optimization across time. This method allows learned dynamics models to plan over longer horizons without the typical computational collapse. BAIR researchers added stochasticity to the process to improve robustness. Practitioners can now optimize complex agent behaviors more efficiently in simulated environments.