Trajectory Optimization via Schr\"{o}dinger Bridge Sampling
We take a new look at the relation between finite-horizon trajectory optimization and Schr\"odinger bridge sampling. Viewed as inference, KL-regularized trajectory optimization is solved by sampling from a Gibbs--Boltzmann distribution whose energy is the trajectory cost, and the adjoint Schr\"odinger bridge sampler (A...