Dynamic stochastic matching problems arise in a variety of recent applications, ranging from ridesharing and online video games to kidney exchange. Such problems are naturally formulated as Markov ...

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 ...

Many real-world problems such as industrial production planning 1,2, traffic signal control 3,4, military strategic decision-making 5,6 and energy management of hybrid electric vehicles 7 can be ...

We propose a dynamic programming algorithm that generates chemical isomers of a given chemical compound with cycles. We represent a chemical compound as a chemical graph and define its feature vector ...

Understand the principles of efficient algorithms for dealing with large scale data sets and be able to select appropriate algorithms for specific problems. Understand and be able to apply the main ...

You could say reactive programming is like functional programming with superpowers. Let's take a look at this dynamic programming style. Reactive programming is an important facet of modern software ...