Abstract: This letter presents a semi-parametric approach for learning safe data-driven control barrier functions (SDD-CBFs) for unknown continuous systems from noisy data. By leveraging optimization ...
A new tool developed by scientists allows real-time monitoring of plant stomata, offering new insights into water-saving strategies that could revolutionize agriculture.
Rapid advances in artificial intelligence, machine learning, and data-driven computational modeling have opened unprecedented opportunities to transform ...
Abstract: This article investigates the optimal distributed formation control for heterogeneous air–ground vehicle systems using a data-efficient, off-policy reinforcement learning algorithm.
GridFM DataKit (gridfm-datakit) is a Python library for generating realistic, diverse, and scalable synthetic datasets for power flow (PF) and optimal power flow (OPF) machine learning solvers. It ...