Researchers have developed a new derivative-free temporal-difference (TD) framework for calibrating black-box simulators. This framework uses one-step transitions from a target system and noisy simulator-generated continuation values, defining the calibration parameter through Bellman orthogonality. The proposed TD algorithms establish convergence and error bounds across various query-noise regimes, revealing a specification-dependent bias phenomenon where bias can vanish under correct simulator specification. AI
RANK_REASON The cluster contains a research paper detailing a new framework for simulator calibration. [lever_c_demoted from research: ic=1 ai=1.0]
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- Bellman orthogonality
- Kiefer-Wolfowitz
- L2
- Polyak--Ruppert
- Student's t-test
- Temporal difference learning
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