Dynamic optimization and optimal control problems form the backbone of numerous applications in engineering, economics and the natural sciences. These methodologies involve determining a time-varying ...

We present a novel method for deriving tight Monte Carlo confidence intervals for solutions of stochastic dynamic programming equations. Taking some approximate solution to the equation as an input, ...

Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...

This course covers reinforcement learning aka dynamic programming, which is a modeling principle capturing dynamic environments and stochastic nature of events. The main goal is to learn dynamic ...

The company is using technology jointly developed with the Nara Institute of Science and Technology to control gas plant ...

This is a preview. Log in through your library . Abstract Honeybee colonies, like organisms, should exhibit optimal design in their temporal pattern of resource allocation to somatic structures. A ...