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Article Dans Une Revue IEEE Transactions on Automatic Control Année : 2022

Risk-sensitive safety analysis using Conditional Value-at-Risk*

Margaret P Chapman
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Insoon Yang
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Marco Pavone
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Claire J Tomlin
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Résumé

This paper develops a safety analysis method for stochastic systems that is sensitive to the possibility and severity of rare harmful outcomes. We define risksensitive safe sets as sub-level sets of the solution to a non-standard optimal control problem, where a random maximum cost is assessed via Conditional Value-at-Risk (CVaR). The objective function represents the maximum extent of constraint violation of the state trajectory, averaged over a given percentage of worst cases. This problem is well-motivated but difficult to solve tractably because the temporal decomposition for CVaR is history-dependent. Our primary theoretical contribution is to derive computationally tractable under-approximations to risk-sensitive safe sets. Our method provides a novel, theoretically guaranteed, parameter-dependent upper bound to the CVaR of a maximum cost without the need to augment the state space. For a fixed parameter value, the solution to only one Markov decision process problem is required to obtain the under-approximations for any family of risk-sensitivity levels. In addition, we propose a second definition for risk-sensitive safe sets and provide a tractable method for their estimation without using a parameter-dependent upper bound. The second definition is expressed in terms
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Dates et versions

hal-04305360 , version 1 (24-11-2023)

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Margaret P Chapman, Riccardo Bonalli, Kevin M. Smith, Insoon Yang, Marco Pavone, et al.. Risk-sensitive safety analysis using Conditional Value-at-Risk*. IEEE Transactions on Automatic Control, 2022, ⟨10.1109/tac.2021.3131149⟩. ⟨hal-04305360⟩
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