dailyai.report

The GRASP planner optimizes long-horizon trajectories by lifting them into virtual states for parallel processing. This approach integrates stochasticity directly into the dynamics to prevent optimization collapse. Researchers at BAIR used this method to make gradient-based planning practical for complex learned environments. It provides a scalable path for agents to plan deeper into the future.