# Approximate dynamic programming using fluid and diffusion approximations with applications to power management

arXiv: https://arxiv.org/abs/1307.1759 · HTML: https://mlsanity.com/paper/1307.1759/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Jul 2013.

## Built on by (most cited first, 1 of 1)

- [Finding Optimal Policy for Queueing Models: New Parameterization](https://mlsanity.com/paper/2206.10073/) (2022)

## Abstract (arXiv)

Neuro-dynamic programming is a class of powerful techniques for approximating the solution to dynamic programming equations. In their most computationally attractive formulations, these techniques provide the approximate solution only within a prescribed finite-dimensional function class. Thus, the question that always arises is how should the function class be chosen? The goal of this paper is to propose an approach using the solutions to associated fluid and diffusion approximations. In order to illustrate this approach, the paper focuses on an application to dynamic speed scaling for power management in computer processors.