Leveraging Imagined Trajectories in Model-Based Reinforcement Learning: Efficient Uncertainty Estimation for Reducing Computational Costs
Effective methods for online estimation of uncertainty in imagined trajectories to reduce the computational cost of frequent replanning in model-based reinforcement learning.