Abstract:Machine learning (ML) provides no guarantee of safe operation in safety-critical systems such as autonomous vehicles. ML decisions are based on data that tends to represent a partial and imprecise knowledge of the environment. Such probabilistic models can output wrong decisions even with 99% of confidence, potentially leading to catastrophic consequences. Moreover, modern ML algorithms such as deep neural networks (DNN) have a high level of uncertainty in their decisions, and their outcomes are not easily exp… Show more
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