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Found 7 papers, 1 papers with code
Finding Failures in High-Fidelity Simulation using Adaptive Stress Testing and the Backward Algorithm
Validating the safety of autonomous systems generally requires the use of high-fidelity simulators that adequately capture the variability of real-world scenarios.
A Survey of Algorithms for Black-Box Safety Validation of Cyber-Physical Systems
Autonomous cyber-physical systems (CPS) can improve safety and efficiency for safety-critical applications, but require rigorous testing before deployment.
Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims
With the recent wave of progress in artificial intelligence (AI) has come a growing awareness of the large-scale impacts of AI systems, and recognition that existing regulations and norms in industry and academia are insufficient to ensure responsible AI development.
Computers and Society
The Adaptive Stress Testing Formulation
Validation is a key challenge in the search for safe autonomy.
Adaptive Stress Testing without Domain Heuristics using Go-Explore
We demonstrate that GE is able to find failures without domain-specific heuristics, such as the distance between the car and the pedestrian, on scenarios that other RL techniques are unable to solve.
Efficient Autonomy Validation in Simulation with Adaptive Stress Testing
During the development of autonomous systems such as driverless cars, it is important to characterize the scenarios that are most likely to result in failure.
Adaptive Stress Testing for Autonomous Vehicles
This paper presents Monte Carlo Tree Search (MCTS) and Deep Reinforcement Learning (DRL) solutions that can scale to large environments.
