Hi, I'm working on a project to implement support for probabilistic programming with models written as Haskell programs. This is similar to Bayesian graphical models (e.g. BUGS, JAGS) and to full probabilistic programming systems like Church / Venture. http://www.bali-phy.org/models.php This project is not very mature, but it is used as the core of the MCMC software mentioned above, which is relatively mature. Probabilistic programs are written using the probability monad. I've implemented a Haskell interpreter in C++ that records execution traces of the Haskell programs. These execution traces depend on some number of (random) variables, and when one of the variables is changed (during MCMC), the parts of the execution trace that depend on the changed variables are invalidated and recomputed. This saves work by not recomputing the probability of the new state from scratch. I can provide DOT graphs of the execution traces if anyone is interested. The problem domain I've been focusing on is evolution of DNA sequences on binary trees. You can see some of the code for that problem domain here: https://github.com/bredelings/BAli-Phy/blob/master/modules/ The code for the interpreter is here: https://github.com/bredelings/BAli-Phy/blob/master/src/computation/ -BenRI