Utilizing Python for Agent-Based Modeling: The Mesa Framework

Jackie Kazil; David Masad; Andrew Crooks

doi:10.1007/978-3-030-61255-9_30

Utilizing Python for Agent-Based Modeling: The Mesa Framework

Jackie Kazil
, David Masad
, Andrew Crooks

Geography

George Mason University
Rebellion Defense

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

184 Scopus citations

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.

Original language	English
Title of host publication	Social, Cultural, and Behavioral Modeling - 13th International Conference, SBP-BRiMS 2020, Proceedings
Editors	Robert Thomson, Halil Bisgin, Christopher Dancy, Ayaz Hyder, Muhammad Hussain
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	308-317
Number of pages	10
ISBN (Print)	9783030612542
DOIs	https://doi.org/10.1007/978-3-030-61255-9_30
State	Published - 2020
Event	13th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2020 - Washington, United States Duration: Oct 18 2020 → Oct 21 2020

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12268 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	13th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2020
Country/Territory	United States
City	Washington
Period	10/18/20 → 10/21/20

Keywords

Agent-based modeling
Complex systems
Framework
Python

Access to Document

10.1007/978-3-030-61255-9_30

Cite this

Kazil, J., Masad, D., & Crooks, A. (2020). Utilizing Python for Agent-Based Modeling: The Mesa Framework. In R. Thomson, H. Bisgin, C. Dancy, A. Hyder, & M. Hussain (Eds.), Social, Cultural, and Behavioral Modeling - 13th International Conference, SBP-BRiMS 2020, Proceedings (pp. 308-317). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12268 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-61255-9_30

Kazil, Jackie ; Masad, David ; Crooks, Andrew. / Utilizing Python for Agent-Based Modeling : The Mesa Framework. Social, Cultural, and Behavioral Modeling - 13th International Conference, SBP-BRiMS 2020, Proceedings. editor / Robert Thomson ; Halil Bisgin ; Christopher Dancy ; Ayaz Hyder ; Muhammad Hussain. Springer Science and Business Media Deutschland GmbH, 2020. pp. 308-317 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{eee4c25f942c42869387ff2360227afb,

title = "Utilizing Python for Agent-Based Modeling: The Mesa Framework",

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{\textquoteright}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.",

keywords = "Agent-based modeling, Complex systems, Framework, Python",

author = "Jackie Kazil and David Masad and Andrew Crooks",

note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 13th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2020 ; Conference date: 18-10-2020 Through 21-10-2020",

year = "2020",

doi = "10.1007/978-3-030-61255-9\_30",

language = "English",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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}

Kazil, J, Masad, D & Crooks, A 2020, Utilizing Python for Agent-Based Modeling: The Mesa Framework. in R Thomson, H Bisgin, C Dancy, A Hyder & M Hussain (eds), Social, Cultural, and Behavioral Modeling - 13th International Conference, SBP-BRiMS 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12268 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 308-317, 13th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2020, Washington, United States, 10/18/20. https://doi.org/10.1007/978-3-030-61255-9_30

Utilizing Python for Agent-Based Modeling: The Mesa Framework. / Kazil, Jackie; Masad, David; Crooks, Andrew.
Social, Cultural, and Behavioral Modeling - 13th International Conference, SBP-BRiMS 2020, Proceedings. ed. / Robert Thomson; Halil Bisgin; Christopher Dancy; Ayaz Hyder; Muhammad Hussain. Springer Science and Business Media Deutschland GmbH, 2020. p. 308-317 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12268 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Utilizing Python for Agent-Based Modeling

T2 - 13th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2020

AU - Kazil, Jackie

AU - Masad, David

AU - Crooks, Andrew

PY - 2020

Y1 - 2020

N2 - 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.

AB - 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.

KW - Agent-based modeling

KW - Complex systems

KW - Framework

KW - Python

UR - https://www.scopus.com/pages/publications/85094174156

U2 - 10.1007/978-3-030-61255-9_30

DO - 10.1007/978-3-030-61255-9_30

M3 - Conference contribution

AN - SCOPUS:85094174156

SN - 9783030612542

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 308

EP - 317

BT - Social, Cultural, and Behavioral Modeling - 13th International Conference, SBP-BRiMS 2020, Proceedings

A2 - Thomson, Robert

A2 - Bisgin, Halil

A2 - Dancy, Christopher

A2 - Hyder, Ayaz

A2 - Hussain, Muhammad

PB - Springer Science and Business Media Deutschland GmbH

Y2 - 18 October 2020 through 21 October 2020

ER -

Kazil J, Masad D, Crooks A. Utilizing Python for Agent-Based Modeling: The Mesa Framework. In Thomson R, Bisgin H, Dancy C, Hyder A, Hussain M, editors, Social, Cultural, and Behavioral Modeling - 13th International Conference, SBP-BRiMS 2020, Proceedings. Springer Science and Business Media Deutschland GmbH. 2020. p. 308-317. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-61255-9_30

Utilizing Python for Agent-Based Modeling: The Mesa Framework

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