Search Results for author:
Found 7 papers, 1 papers with code
Adaptive Stress Testing of Trajectory Predictions in Flight Management Systems
To find failure events and their likelihoods in flight-critical systems, we investigate the use of an advanced black-box stress testing approach called adaptive stress testing.
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.
Scalable Autonomous Vehicle Safety Validation through Dynamic Programming and Scene Decomposition
In this work, we present a new safety validation approach that attempts to estimate the distribution over failures of an autonomous policy using approximate dynamic programming.
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.
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.
Interpretable Categorization of Heterogeneous Time Series Data
In particular, when a grammar based on temporal logic is used, we show that GBDTs can be used for the interpretable classi cation of high-dimensional and heterogeneous time series data.
Predicting the behavior of interacting humans by fusing data from multiple sources
Multi-fidelity methods combine inexpensive low-fidelity simulations with costly but highfidelity simulations to produce an accurate model of a system of interest at minimal cost.
