SPAIS minimizes the forward KL divergence between a state-dependent sequential proposal and a relaxed failure distribution, achieving more accurate failure probability estimates than baselines on four systems.
Self-driving cars: A survey
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Failure Probability Estimation for Black-Box Autonomous Systems using State-Dependent Importance Sampling Proposals
SPAIS minimizes the forward KL divergence between a state-dependent sequential proposal and a relaxed failure distribution, achieving more accurate failure probability estimates than baselines on four systems.