Interoperability and integration testing methods for IoT systems: A systematic mapping study
M Bures, M Klima, V Rechtberger, X Bellekens… - … conference on software …, 2020 - Springer
The recent active development of Internet of Things (IoT) solutions in various domains has
led to an increased demand for security, safety, and reliability of these systems. Security and …
led to an increased demand for security, safety, and reliability of these systems. Security and …
Runtime monitors for Markov decision processes
We investigate the problem of monitoring partially observable systems with nondeterministic
and probabilistic dynamics. In such systems, every state may be associated with a risk, eg …
and probabilistic dynamics. In such systems, every state may be associated with a risk, eg …
Benchmarking Combinations of Learning and Testing Algorithms for Automata Learning
Automata learning enables model-based analysis of black-box systems by automatically
constructing models from system observations, which are often collected via testing. The …
constructing models from system observations, which are often collected via testing. The …
Learning finite state models from recurrent neural networks
Explaining and verifying the behavior of recurrent neural networks (RNNs) is an important
step towards achieving confidence in machine learning. The extraction of finite state models …
step towards achieving confidence in machine learning. The extraction of finite state models …
A framework for identification and validation of affine hybrid automata from input-output traces
Automata-based modeling of hybrid and cyber-physical systems (CPS) is an important
formal abstraction amenable to algorithmic analysis of its dynamic behaviors, such as in …
formal abstraction amenable to algorithmic analysis of its dynamic behaviors, such as in …
Safe and secure future AI-driven railway technologies: challenges for formal methods in railway
In 2020, the EU launched its sustainable and smart mobility strategy, outlining how it plans
to have a 90% reduction in transport emission by 2050. Central to achieving this goal will be …
to have a 90% reduction in transport emission by 2050. Central to achieving this goal will be …
Modalas: Model-driven assurance for learning-enabled autonomous systems
MA Langford, KH Chan, JE Fleck… - 2021 ACM/IEEE 24th …, 2021 - ieeexplore.ieee.org
Increasingly, safety-critical systems include artificial intelligence and machine learning
components (ie, Learning-Enabled Components (LECs)). However, when behavior is …
components (ie, Learning-Enabled Components (LECs)). However, when behavior is …
Learning Environment Models with Continuous Stochastic Dynamics
Solving control tasks in complex environments automatically through learning offers great
potential. While contemporary techniques from deep reinforcement learning (DRL) provide …
potential. While contemporary techniques from deep reinforcement learning (DRL) provide …
A roadside decision-making methodology based on deep reinforcement learning to simultaneously improve the safety and efficiency of merging zone
J Hu, X Li, Y Cen, Q Xu, X Zhu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The safety and efficiency of the merging zone is particularly important for traffic networks.
Although autonomous vehicle improves the safety and efficiency from vehicle view, traffic …
Although autonomous vehicle improves the safety and efficiency from vehicle view, traffic …
MoDALAS: addressing assurance for learning-enabled autonomous systems in the face of uncertainty
Increasingly, safety-critical systems include artificial intelligence and machine learning
components (ie, learning-enabled components (LECs)). However, when behavior is learned …
components (ie, learning-enabled components (LECs)). However, when behavior is learned …