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Found 6 papers, 0 papers with code
Learning Safety Filters for Unknown Discrete-Time Linear Systems
A learning-based safety filter is developed for discrete-time linear time-invariant systems with unknown models subject to Gaussian noises with unknown covariance.
An expressiveness hierarchy of Behavior Trees and related architectures
In this paper we provide a formal framework for comparing the expressive power of Behavior Trees (BTs) to other action selection architectures.
Safe Learning of Uncertain Environments
We show that with an arbitrarily large probability we can guarantee that the state will remain in the safe set, while learning and control are carried out simultaneously, provided that a feasible solution exists for the optimization problem.
On modularity in reactive control architectures, with an application to formal verification
We use a Linear Temporal Logic-based verification scheme to verify the correctness of this structure, and then show how one can modify modules while preserving its correctness.
A principled analysis of Behavior Trees and their generalisations
As complex autonomous robotic systems become more widespread, the need for transparent and reusable Artificial Intelligence (AI) designs becomes more apparent.
Suicide Risk Assessment with Multi-level Dual-Context Language and BERT
Mental health predictive systems typically model language as if from a single context (e. g. Twitter posts, status updates, or forum posts) and often limited to a single level of analysis (e. g. either the message-level or user-level).
