Bigraphs are a universal computational modelling formalism for the spatial and temporal evolution of a system in which entities can be added and removed. We extend bigraphs to probabilistic bigraphs, and then again to action bigraphs, which include non-determinism and rewards. The extensions are implemented in the BigraphER toolkit and illustrated through examples of virus spread in computer networks and data harvesting in wireless sensor systems. BigraphER also supports the existing stochastic bigraphs extension of Krivine et al., and using BigraphER we give, for the first time, a direct implementation of the membrane budding model used to motivate stochastic bigraphs.

Bigraphs 是一种通用的计算建模形式，用于系统的空间和时间演化，其中可以添加和删除实体。我们将二图扩展到概率二图，然后再扩展到动作二图，其中包括非确定性和奖励。这些扩展在 BigraphER 工具包中实现，并通过计算机网络中的病毒传播和无线传感器系统中的数据收集示例进行说明。BigraphER 还支持 Krivine 等人现有的随机二图扩展，并且使用 BigraphER，我们首次直接实现了用于激励随机二图的膜芽模型。