Strategies for simulator recalibration under data drift
In brief
- Four recalibration strategies for simulators are compared under real-world data drift.
- Continuous exploration and randomized experimentation can outperform passive adaptation depending on costs and drift visibility.
- Partially observed and misspecified simulators require adjustments to avoid suboptimal policies.
This study compares four strategies to recalibrate a simulator facing real-world data drift. It evaluates continuous exploration, randomized experimentation, and passive adaptation, considering costs and data limitations.
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