Agents.jl：一款高性能且功能齐全的基于代理的建模软件，代码复杂性最低
Agents.jl: A performant and feature-full agent based modelling software of minimal code complexity
摘要：
基于Agent的建模是一种仿真方法，其中自主智能体与它们的环境以及彼此之间进行交互，给定一组预定义的规则。它是一种用于建模和模拟复杂系统（如社会经济问题）的集成方法。由于基于代理的模型不是由简单而简洁的数学方程描述的，因此生成它们的代码通常是复杂的，大型的和缓慢的。在这里，我们提出的Agents.jl，一个基于Julia的软件，提供了一个ABM分析平台，最小的代码复杂性。我们比较我们的软件与一些最流行的ABM软件在其他程序设计语言。我们发现Agents.jl不仅是性能最好的，而且是最不复杂的软件，它提供了与竞争对手相同（有时更多）的功能，而用户需要的输入更少。Agents.jl还与整个Julia生态系统进行了出色的集成，包括交互式应用程序、微分方程、参数优化等。这消除了Agents.jl中的任何“扩展库”需求，这在许多其他工具中是至关重要的。
英文摘要：
Agent based modelling is a simulation method in which autonomous agents interact with their environment and one another, given a predefined set of rules. It is an integral method for modelling and simulating complex systems, such as socio-economic problems. Since agent based models are not described by simple and concise mathematical equations, code that generates them is typically complicated, large, and slow. Here we present Agents.jl, a Julia-based software that provides an ABM analysis platform with minimal code complexity. We compare our software with some of the most popular ABM software in other programming languages. We find that Agents.jl is not only the most performant, but also the least complicated software, providing the same (and sometimes more) features as the competitors with less input required from the user. Agents.jl also integrates excellently with the entire Julia ecosystem, including interactive applications, differential equations, parameter optimization, and more. This removes any ``extensions library'' requirement from Agents.jl, which is paramount in many other tools.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
