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Agent-based modeling is a computational methodology used in social science, biology, and other fields, which involves simulating the behavior and interaction of many autonomous entities, or agents, over time. There is currently a hole in this area in Pythonâs robust and growing scientific ecosystem. Mesa is a new open-source, Apache 2.0 licensed package meant to fill that gap. It allows users to quickly create agent-based models using built-in core components (such as agent schedulers and spatial grids) or customized implementations; visualize them using a browser-based interface; and analyze their results using Pythonâs data analysis tools. Its goal is to be a Python 3-based alternative to other popular frameworks based in other languages such as NetLogo, Repast, or MASON. Since the framework is being built from scratch it is able to incorporate lessons from other tools. In this paper, we present Mesa's core features and demonstrate them with a simple example model.1
Masad et al. (Thu,) studied this question.