jsdp: a Java Stochastic DP Library
This provides a new software library for researchers and practitioners in operations research and AI to implement stochastic dynamic programming models, but it is incremental as it builds on existing Java features and MapReduce concepts.
The authors tackled the problem of modeling and solving stochastic dynamic programs by developing jsdp, a Java library that leverages functional programming constructs and the MapReduce framework, resulting in a general-purpose tool for decision-making under uncertainty.
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.