Model Predictive Path Integral Control as a Quantum Query Problem

This work reformulates Model Predictive Path Integral Control, which uses trajectory samples to update a control policy, into a quantum query problem. By encoding the update from these samples as success probabilities, it shows that this approach can achieve a quadratic improvement in query dependence over classical Monte Carlo methods.

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