Cite mango for python

If you use mango for your research please cite our SoftwareX publication as follows.

For LaTeX

@article{SCHRAGE2024101791,
    title = {mango: A modular python-based agent simulation framework},
    journal = {SoftwareX},
    volume = {27},
    pages = {101791},
    year = {2024},
    issn = {2352-7110},
    doi = {https://doi.org/10.1016/j.softx.2024.101791},
    url = {https://www.sciencedirect.com/science/article/pii/S2352711024001626},
    author = {Rico Schrage and Jens Sager and Jan Philipp Hörding and Stefanie Holly},
    keywords = {Agent, Communication, Modular software development, Python, Multi-agent system, Energy application, Complex systems},
}

Otherwise

Schrage, R., Sager, J., Hörding, J. P., & Holly, S. (2024). mango: A modular python-based agent simulation framework. SoftwareX, 27, 101791. doi:10.1016/j.softx.2024.101791

Publications using mango

Here are some selected publications using mango.

• Stark, S., Frost, E., & Nebel-Wenner, M. (2024). Distributed Multi-objective Optimization in Cyber-Physical Energy Systems. ACM SIGENERGY Energy Informatics Review, 4(2), 7-18.
• Frost, E., Radtke, M., Nebel-Wenner, M., Oest, F., & Stark, S. (2024). cosima-mango: Investigating Multi-Agent System robustness through integrated communication simulation. Available at SSRN 4625704.
• Heess, P., Holly, S., Körner, M. F., Nieße, A., Radtke, M., Schick, L., … & Zwede, T. (2025). A multi-agent approach with verifiable and data-sovereign information flows for decentralizing redispatch in distributed energy systems. Energy Informatics, 8(1), 24.
• Frost, E., & Nieße, A. (2024, November). Communication Incidents in Self-Organising Cyber-Physical Energy Systems: Assessing Robustness. In 2024 5th International Conference on Communications, Information, Electronic and Energy Systems (CIEES) (pp. 1-6). IEEE.
• Veith, E. M., & Frost, E. COVER ME: SAFEGUARDING MULTI-AGENT SYSTEMS WITH DEEP REINFORCEMENT LEARNING FOR RESILIENT GRID OPERATION.
• Valko, D., Alsharif, S., Tolk, D., & Grimm, T. MASSCA: SCALABLE MULTI-AGENT SYSTEM FRAMEWORK FOR SMART POWER CELL CO-SIMULATION.