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fix multiple citations in joss paper #2692

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Feb 15, 2025
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fix multiple citations in joss paper #2692

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2 changes: 1 addition & 1 deletion paper/paper.md
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@@ -57,7 +57,7 @@ preferred-citation: article
Mesa is an open-source Python framework for agent-based modeling (ABM) that enables researchers to create, analyze, and visualize agent-based simulations. Mesa provides a comprehensive set of tools and abstractions for modeling complex systems, with capabilities spanning from basic agent management to sophisticated representation of spaces where agents interact. First released in 2014 and published in @masad2015 (with updates published in @kazil2020), this paper highlights advancements and presents Mesa in its current version (3.1.4) as of 2025.

# Statement of need
Agent-based models (ABMs) are composed of autonomous heterogeneous agents interacting locally with other agents. These interactions give rise to emergent phenomena. The aggregate dynamics of a system under study emerge from these local interactions [@epstein_axtell_1996, @epstein1999]. This type of modeling quickly grew more sophisticated, requiring frameworks to execute them. This led to the establishment of [NetLogo](https://ccl.northwestern.edu/netlogo/) and [MASON](https://cs.gmu.edu/~eclab/projects/mason/).
Agent-based models (ABMs) are composed of autonomous heterogeneous agents interacting locally with other agents. These interactions give rise to emergent phenomena. The aggregate dynamics of a system under study emerge from these local interactions [@epstein_axtell_1996; @epstein1999]. This type of modeling quickly grew more sophisticated, requiring frameworks to execute them. This led to the establishment of [NetLogo](https://ccl.northwestern.edu/netlogo/) and [MASON](https://cs.gmu.edu/~eclab/projects/mason/).

However, before Mesa, there was no modern Python-based framework for ABMs that integrated with the scientific Python ecosystem. Since its creation in 2014, Mesa has been applied to modeling everything from economics and sociology to ecology and epidemiology and has been cited in more than 500 papers and 800 authors. With its most recent major release, Mesa has advanced usability and stabilized functionality. These features include enhanced management of agents, data collection advancements, an improved visualization framework, and making it easier for researchers to create and analyze complex simulations.