PSL is a collection of open-source models and data preparation routines for policy analysis. Learn more about our organization and our mission.

A library of open source models for public policy analysis - Policy Simulation Library

Probabilistic soft logic (PSL) is a machine learning framework for developing probabilistic models. PSL models are easy to use and fast. You can define models using a straightforward logical syntax and solve them with fast convex optimization.

We have a collection of open-source models and data preparation routines for policy analysis. PSL is developed by a community of technical contributors. Learn how to contribute to library projects or add a new project to the library.

The Policy Simulation Library (PSL) is an open source software library for public-policy decisionmaking. The models in PSL are developed by independent projects that conform to PSL criteria for transparency. Modeling projects may also adopt PSL's criteria for interoperability and community building, which take the form of suggestions for ...

The Policy Simulation Library (PSL) is a collection of models and other software for public-policy decisionmaking. PSL is developed by independent projects that meet standards for transparency and accessibility.

Probabilistic soft logic (PSL) is a machine learning framework for developing probabilistic models. PSL models are easy to use and fast. You can define models using a straightforward logical syntax and solve them with fast convex optimization.

PolicyEngine US is a new web app for computing the impact of US tax and benefit policy. Washington, DC open-source modeling workshop, March 25, 2022, 8:30am-1:00pm, Martin Luther King, Jr. Memorial Library. Highlights from the Policy Simulation Library in 2021.

PSL combines two tools: first-order logic, with its ability to succinctly represent complex phenomena, and probabilistic graphical models, which capture the uncertainty and incompleteness inherent in real-world knowledge. More specifically, PSL uses "soft" logic as its logical component and Markov random fields as its statistical model.

Data structures for executing examples with models in the Policy Simulation Library. We welcome community contributions.