Skip to main navigation Skip to search Skip to main content

monviso: A Python Package for Solving Monotone Variational Inequalities

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

4 Downloads (Pure)

Abstract

In this paper, we present monviso (monotone variational inequalities solver), a novel open-source Python package for solving monotone variational inequalities. We detail the package’s structure and baseline functionality, discussing a simple example that illustrates the essential methods and parameters. Moreover, we characterize how the proximal operator, which is the foundation of many iterative schemes, is handled through cvxpy, an open-source Python library for convex optimization. We list the available algorithms and describe the basic implementation of any general iterative method to enable users to build additional and (possibly new) algorithms. Finally, we illustrate several examples of possible use cases for monviso, showcasing the different applications the package can support across various fields, including control, optimization, dynamic game theory, and machine learning.
Original languageEnglish
Title of host publicationProceedings of the 23rd European Control Conference (ECC 2025)
PublisherIEEE
Pages1708-1713
Number of pages6
ISBN (Electronic)978-3-907144-12-1
DOIs
Publication statusPublished - 2025
Event23rd European Control Conference (ECC 2025) - Thessaloniki, Greece
Duration: 24 Jun 2025 → 27 Jun 2025

Conference

Conference23rd European Control Conference (ECC 2025)
Country/TerritoryGreece
CityThessaloniki
Period24/06/25 → 27/06/25

Fingerprint

Dive into the research topics of 'monviso: A Python Package for Solving Monotone Variational Inequalities'. Together they form a unique fingerprint.

Cite this