A KL-divergence trust-region formulation for sampling-based MPC replaces heuristic hyperparameter adaptation with Lagrangian-optimal updates and improves convergence when combined with deterministic LCD sampling.
High-dimensional integration: The quasi-Monte Carlo way
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Sampling-based Model Predictive Control Using Trust Regions
A KL-divergence trust-region formulation for sampling-based MPC replaces heuristic hyperparameter adaptation with Lagrangian-optimal updates and improves convergence when combined with deterministic LCD sampling.