This is interesting. We've been thinking quite a bit about parallelising our model, but haven't managed it yet. The problem is that although our agents are mostly independent of each other, they all depend on the shared state of the world (and modify this, too).

Therefore, if we were to use a multiprocessing setup, we would have to be able to lock the world object when a process is writing to it; and furthermore, find a way to pass it around in memory so that all processes have read access to it. While we know that it should be technically doable, the latency overhead of the latter has proven prohibitively high.

Yeah, for some models, especially small-scale ones, it can be hard to get a performance gain. There are actually ways of avoiding the locking, e.g., by staging the desired actions and then carrying them out afterwards, resolving conflicts as needed. We actually have a paper on this as well, but I'm going to stop pushing my research at this point ;)