Adaptive Stress Testing: Finding Likely Failure Events with Reinforcement Learning

Finding the most likely path to a set of failure states is important to the analysis of safety-critical systems that operate over a sequence of time steps, such as aircraft collision avoidance systems and autonomous cars. In many applications such as autonomous driving, failures cannot be completely...

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Vydáno v:	The Journal of artificial intelligence research Ročník 69; s. 1165 - 1201
Hlavní autoři:	Lee, Ritchie, Mengshoel, Ole J., Saksena, Anshu, Gardner, Ryan W., Genin, Daniel, Silbermann, Joshua, Owen, Michael, Kochenderfer, Mykel J.
Médium:	Konferenční příspěvek Journal Article
Jazyk:	angličtina
Vydáno:	Ames Research Center AI Access Foundation, Inc 06.12.2020 AI Access Foundation
Témata:	Aircraft Aircraft accidents Artificial intelligence Autonomous cars Collision avoidance Collisions Computer simulation Cybernetics, Artificial Intelligence And Robotics Failure Failure analysis Flight data recorders Learning Markov processes Midair collisions Pseudorandom Safety critical Search algorithms Statistics And Probability Systems Analysis And Operations Research Adaptive Stress Testing Reinforcement Learning Collision Avoidance Verification And Validation Acas X Safety-Critical Systems
ISSN:	1076-9757, 1943-5037, 1076-9757
On-line přístup:	Získat plný text
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