Loading Now

Summary of Proceedings Of the 2024 Xcsp3 Competition, by Gilles Audemard et al.


Proceedings of the 2024 XCSP3 Competition

by Gilles Audemard, Christophe Lecoutre, Emmanuel Lonca

First submitted to arxiv on: 28 Nov 2024

Categories

  • Main: Artificial Intelligence (cs.AI)
  • Secondary: None

     Abstract of paper      PDF of paper


GrooveSquid.com Paper Summaries

GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!

Summary difficulty Written by Summary
High Paper authors High Difficulty Summary
Read the original abstract here
Medium GrooveSquid.com (original content) Medium Difficulty Summary
The 2024 XCSP3 Competition, a benchmarking event for constraint solvers, was held as part of the CP’24 conference. The competition featured submissions from various constraint solver implementations, which were evaluated based on their performance in solving problems from diverse domains, including AI and machine learning. The paper presents the results of this competition, highlighting the strengths and weaknesses of each participating solver.
Low GrooveSquid.com (original content) Low Difficulty Summary
The 2024 XCSP3 Competition is a benchmarking event for constraint solvers that took place during the CP’24 conference. This competition helps developers improve their algorithms by providing a platform to test their constraint solving abilities. The results are important because they show which solvers perform well in different problem domains, including AI and machine learning.

Keywords

» Artificial intelligence  » Machine learning