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A DSL for continuous-time agent-based modeling and simulation

机译:DSL,用于基于代理的连续时间建模和仿真

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Most state-of-the-art agent-based modeling and simulation (ABMS) frameworks offer a way to describe agent behavior in a programming language. Whereas these frameworks support easy development of time-stepped models, continuous-time models can only be implemented by manually scheduling and retracting events as part of the agent behavior. To facilitate a separation of concerns into model- and simulation-specific code for continuous-time ABMS, we propose an embedded domain-specific language, which allows describing agent behavior concisely, and corresponding simulation algorithms, which allow executing continuous-time models. The language style and the algorithms are adapted from rule-based modeling languages for Continuous-Time Markov Chains and Stochastic Simulation Algorithm variants. We implemented prototypes of the modeling language and simulation algorithms based on Repast Simphony.
机译:大多数最新的基于代理的建模和仿真(ABMS)框架提供了一种以编程语言描述代理行为的方法。这些框架支持轻松开发时间步进模型,而连续时间模型只能通过手动调度和撤回事件(作为代理行为的一部分)来实现。为了便于将关注点分离为连续时间ABMS的模型代码和特定于仿真的代码,我们提出了一种嵌入式领域特定的语言(该语言可以简洁地描述代理行为)和相应的模拟算法(该算法可以执行连续时间模型)。语言样式和算法从基于规则的建模语言改编而来,用于连续时间马尔可夫链和随机模拟算法变体。我们基于Repast Simphony实现了建模语言和仿真算法的原型。

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