# jsdp: a Java Stochastic DP Library

arXiv: https://arxiv.org/abs/2209.09979 · HTML: https://mlsanity.com/paper/2209.09979/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 21 references that are in the map.
- First posted on arXiv 20 Sep 2022.

## Builds on (most cited first, 2 of 2)

- [The Dynamic Bowser Routing Problem](https://mlsanity.com/paper/1705.10609/) (2017)
- [Efficient Stochastic Programming in Julia](https://mlsanity.com/paper/1909.10451/) (2019)

## Abstract (arXiv)

Stochastic Programming is a framework for modelling and solving problems of decision making under uncertainty. Stochastic Dynamic Programming is a branch of Stochastic Programming that takes a "functional equation" approach to the discovery of optimal policies. By leveraging constructs - lambda expressions, functional interfaces, collections and aggregate operators - implemented in Java to operationalise the MapReduce framework, jsdp provides a general purpose library for modelling and solving Stochastic Dynamic Programs.