Metareasoning optimizes modular systems by dynamically adjusting configurations.
problem Maximizing system utility in high-stakes tasks with modular subsystems.
method Employing reinforcement learning with rich contextual representations to dynamically adjust module configurations.
result Significant improvement in system performance across various reinforcement learning techniques.