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A Model-Free Sampling Method for Estimating Basins of Attraction Using Hybrid Active Learning (HAL)
The proposed method is based upon hybrid active learning (HAL) and is designed to find and label the "informative" samples, which efficiently determine the boundary of BoA.
Constrained Attractor Selection Using Deep Reinforcement Learning
This paper describes an approach for attractor selection (or multi-stability control) in nonlinear dynamical systems with constrained actuation.
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