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 ...

We present an Approximate Dynamic Programming (ADP) approach for the multidimensional knapsack problem (MKP). We approximate the value function (a) using parametric and nonparametric methods and (b) ...

As technology continues to evolve, the barrier to entry for programming seems to be gradually lowering. The launch of GPT-5-Codex not only provides programmers with more powerful ...

Dynamic programming algorithms are developed for optimal capital allocation subject to budget constraints. We extend the work of Weingartner [17] and Weingartner and Ness [19] by including multilevel ...