# Cross Language Soccer Framework: An Open Source Framework for the RoboCup 2D Soccer Simulation

arXiv: https://arxiv.org/abs/2406.05621 · HTML: https://mlsanity.com/paper/2406.05621/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 30 references that are in the map.
- First posted on arXiv 9 Jun 2024.

## Builds on (most cited first, 9 of 9)

- [OpenAI Gym](https://mlsanity.com/paper/1606.01540/) (2016)
- [Google Research Football: A Novel Reinforcement Learning Environment](https://mlsanity.com/paper/1907.11180/) (2019)
- [Gliders2d: Source Code Base for RoboCup 2D Soccer Simulation League](https://mlsanity.com/paper/1812.10202/) (2018)
- [Cyrus2D base: Source Code Base for RoboCup 2D Soccer Simulation League](https://mlsanity.com/paper/2211.08585/) (2022)
- [RoboCup 2D Soccer Simulation League: Evaluation Challenges](https://mlsanity.com/paper/1706.04315/) (2017)
- [Disruptive innovations in RoboCup 2D Soccer Simulation League: from Cyberoos'98 to Gliders2016](https://mlsanity.com/paper/1612.00947/) (2016)
- [Fractals2019: Combinatorial Optimisation with Dynamic Constraint Annealing](https://mlsanity.com/paper/1909.01788/) (2019)
- [Pyrus Base: An Open Source Python Framework for the RoboCup 2D Soccer Simulation](https://mlsanity.com/paper/2307.16875/) (2023)
- [Engineering Features to Improve Pass Prediction in Soccer Simulation 2D Games](https://mlsanity.com/paper/2401.03410/) (2024)

## Built on by (most cited first, 1 of 1)

- [R2D-RL: A RoboCup 2D Soccer Environment for Multi-Agent Reinforcement Learning](https://mlsanity.com/paper/2606.18786/) (2026)

## Abstract (arXiv)

RoboCup Soccer Simulation 2D (SS2D) research is hampered by the complexity of existing Cpp-based codes like Helios, Cyrus, and Gliders, which also suffer from limited integration with modern machine learning frameworks. This development paper introduces a transformative solution a gRPC-based, language-agnostic framework that seamlessly integrates with the high-performance Helios base code. This approach not only facilitates the use of diverse programming languages including CSharp, JavaScript, and Python but also maintains the computational efficiency critical for real time decision making in SS2D. By breaking down language barriers, our framework significantly enhances collaborative potential and flexibility, empowering researchers to innovate without the overhead of mastering or developing extensive base codes. We invite the global research community to leverage and contribute to the Cross Language Soccer (CLS) framework, which is openly available under the MIT License, to drive forward the capabilities of multi-agent systems in soccer simulations.