  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 probablistic 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.
