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International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation

SBP-BRiMS 2020: Social, Cultural, and Behavioral Modeling pp 308–317Cite as

Utilizing Python for Agent-Based Modeling: The Mesa Framework

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12268))

Abstract

Mesa is an agent-based modeling framework written in Python. Originally started in 2013, it was created to be the go-to tool in for researchers wishing to build agent-based models with Python. Within this paper we present Mesa’s design goals, along with its underlying architecture. This includes its core components: 1) the model (Model, Agent, Schedule, and Space), 2) analysis (Data Collector and Batch Runner) and the visualization (Visualization Server and Visualization Browser Page). We then discuss how agent-based models can be created in Mesa. This is followed by a discussion of applications and extensions by other researchers to demonstrate how Mesa design is decoupled and extensible and thus creating the opportunity for a larger decentralized ecosystem of packages that people can share and reuse for their own needs. Finally, the paper concludes with a summary and discussion of future development areas for Mesa.

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Notes

  1. 1.

    We chose the name Mesa for three weak reasons: (1) It sounded like Mason, (2) It evoked the mesas around Santa Fe, the location of the Santa Fe Institute and home to much complexity research, and (3) It was a short and memorable name that was available on the Python Package Index (PyPI).

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Acknowledgements

While originally developed by Jackie Kazil and David Masad, Mesa has had over 70 contributors. A special thank you to Corvince, rht, Taylor Mulch, and Tom Pike for their contributions or continuing support to Mesa.

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Authors and Affiliations

  1. George Mason University, Fairfax, VA, 22020, USA

    Jackie Kazil, David Masad & Andrew Crooks

  2. Rebellion Defense, Washington DC, 20001, USA

    Jackie Kazil

Authors
  1. Jackie Kazil
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  2. David Masad
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  3. Andrew Crooks
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Corresponding author

Correspondence to Jackie Kazil .

Editor information

Editors and Affiliations

  1. United States Military Academy, West Point, NY, USA

    Robert Thomson

  2. University of Michigan-Flint, Flint, MI, USA

    Halil Bisgin

  3. Bucknell University, Lewisburg, PA, USA

    Christopher Dancy

  4. The Ohio State University, Columbus, OH, USA

    Ayaz Hyder

  5. University of Arkansas at Little Rock, Little Rock, AR, USA

    Muhammad Hussain

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Kazil, J., Masad, D., Crooks, A. (2020). Utilizing Python for Agent-Based Modeling: The Mesa Framework. In: Thomson, R., Bisgin, H., Dancy, C., Hyder, A., Hussain, M. (eds) Social, Cultural, and Behavioral Modeling. SBP-BRiMS 2020. Lecture Notes in Computer Science(), vol 12268. Springer, Cham. https://doi.org/10.1007/978-3-030-61255-9_30

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  • DOI: https://doi.org/10.1007/978-3-030-61255-9_30

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-61254-2

  • Online ISBN: 978-3-030-61255-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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