  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.
