The specificity and predictability of Watson–Crick base pairing make DNA a powerful and versatile material for engineering at the nanoscale. This has enabled the construction of a diverse and rapidly ...

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 ...

Dynamic Programming and Optimal Control is offered within DMAVT and attracts in excess of 300 students per year from a wide variety of disciplines. It is an integral part of the Robotics, System and ...

The paper shows how the technique of dynamic programming was applied to the problem of determining the optimum mix of widths of steel used to `pack' a transformer coil. The approach enables the ...

In Part 2 of this series, MathWorks' Heather Gorr details how to take advantage of Python-based AI and ML libraries via MATLAB. This illustration shows the integration of MATLAB and Simulink with ...

Mathematical Background: We expect that the student is comfortable with basic mathematics at the level of a U.S. first-year college STEM student. This includes basic notions such as sets and functions ...

P. "Venkat" Venkataraman of Brighton, associate professor of mechanical engineering in the Kate Gleason College of Engineering at Rochester Institute of Technology, wrote the textbook, Applied ...