The program used inverse graphics as the basis of its inference method, and was built using the Picture package in Julia.
[5][6] The Gen probabilistic programming library (also written in Julia) has been applied to vision and robotics tasks.
[15][16] The language for WinBUGS was implemented to perform Bayesian computation using Gibbs Sampling and related algorithms.
The same BUGS language may be used to specify Bayesian models for inference via different computational choices ("samplers") and conventions or defaults, using a standalone program WinBUGS (or related R packages, rbugs and r2winbugs) and JAGS (Just Another Gibbs Sampler, another standalone program with related R packages including rjags, R2jags, and runjags).
More recently, other languages to support Bayesian model specification and inference allow different or more efficient choices for the underlying Bayesian computation, and are accessible from the R data analysis and programming environment, e.g.: Stan, NIMBLE and NUTS.
A PRM is usually developed with a set of algorithms for reducing, inference about and discovery of concerned distributions, which are embedded into the corresponding PRPL.