Sequential sampling models (SSMs) are a widely used framework describing decision-making as a stochastic, dynamic process of evidence accumulation. SSMs popularity across cognitive science has driven the development of various software packages that lower the barrier for simulating, estimating, and comparing existing SSMs. Here, we present a software tool, SequentialSamplingModels.jl (SSM.jl), designed to make SSM simulations more accessible to Julia users, and to integrate with the Julia ecosystem. We demonstrate the basic use of SSM.jl for simulation, plotting, and Bayesian inference.

翻译：顺序采样模型（SSMs）是一种广泛使用的理论框架，它将决策描述为证据积累的随机动态过程。SSMs在认知科学领域的普及推动了多种软件包的发展，这些软件包降低了模拟、估计和比较现有SSMs的门槛。本文介绍一款软件工具——SequentialSamplingModels.jl（SSM.jl），旨在使Julia用户更便捷地进行SSM模拟，并与Julia生态系统集成。我们展示了SSM.jl在模拟、绘图和贝叶斯推断方面的基本使用方法。