MPPI is recovered as unit-step preconditioned gradient descent on a reduced free-energy objective over parametric sampling distributions, with descent guarantees when the preconditioned Hessian is bounded.
Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation (CMA- ES)
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Model Predictive Path Integral Control as Preconditioned Gradient Descent
MPPI is recovered as unit-step preconditioned gradient descent on a reduced free-energy objective over parametric sampling distributions, with descent guarantees when the preconditioned Hessian is bounded.