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jsdp: a Java Stochastic Dynamic Programming Library

2022-09-20 20:20:20
Roberto Rossi
arXiv_AI
     
Abstract

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.

Abstract (translated)

URL

https://arxiv.org/abs/2209.09979

PDF

https://arxiv.org/pdf/2209.09979.pdf

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