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Koopman-based Control for Stochastic Systems: Application to Enhanced Sampling

Optimization and Control 2024-10-15 v1 Dynamical Systems Computational Physics
Authors: Lei Guo , Jan Heiland , Feliks Nüske
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Abstract

We present a data-driven approach to use the Koopman generator for prediction and optimal control of control-affine stochastic systems. We provide a novel conceptual approach and a proof-of-principle for the determination of optimal control policies which accelerate the simulation of rare events in metastable stochastic systems.

Keywords

koopman operator theory stochastic control dynamic programming

Cite

@article{arxiv.2410.09452,
  title  = {Koopman-based Control for Stochastic Systems: Application to Enhanced Sampling},
  author = {Lei Guo and Jan Heiland and Feliks Nüske},
  journal= {arXiv preprint arXiv:2410.09452},
  year   = {2024}
}

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