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 ...

The background for this paper is a dynamic programming model with a Borel state space and compact action sets. A new simple proof of the compactness of a space of measures corresponding to randomized ...

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 ...

In this course we introduce the fundamentals of Deep Reinforcement Learning from scratch starting from its roots in Dynamic Programming and optimal control, and ending with some of the most popular ...

Covers the fundamentals of algorithms and various algorithmic strategies, including time and space complexity, sorting algorithms, recurrence relations, divide and conquer algorithms, greedy ...