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Taming Lagrangian Chaos with Multi-Objective Reinforcement Learning
We consider the problem of two active particles in 2D complex flows with the multi-objective goals of minimizing both the dispersion rate and the energy consumption of the pair.
Reinforcement learning for pursuit and evasion of microswimmers at low Reynolds number
We consider a model of two competing microswimming agents engaged in a pursue-evasion task within a low-Reynolds-number environment.
Effective models and predictability of chaotic multiscale systems via machine learning
We scrutinize the use of machine learning, based on reservoir computing, to build data-driven effective models of multiscale chaotic systems.
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