What began with a focus on weather forecasting has evolved toward addressing errors in scientific modeling. In the collaborative environment of the Penn State Institute for Computational and Data ...

Conclusions We have presented a discrete approach to data-based dimension reduction and stochastic parametrization in which the problem is consistently treated as discrete, obviating earlier ...

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Details Abstract: Integral reinforcement learning (IntRL) demands the precise computation of the utility function's integral at its policy evaluation (PEV) stage. This is achieved through quadrature ...