[musesum]

From Bill Gathan: http://www.codenewbie.org/blogs/object-oriented-programming-...

Michael Fogus, author of “Functional JavaScript”, suggests in his blog post “FP vs OO, from the trenches” (http://blog.fogus.me/2013/07/22/fp-vs-oo-from-the-trenches/) that when he deals with data about people, FP works well, but when he tries to simulate people, OOP works well.

I wonder about shape of the data as it moves from domain -> range? How would they map to machine and biological models for learning? First guess is the that ML maps well onto FP; for CNNs, the data progresses synchronously from one layer to the next. For Bio, state is asynchronous; neurons, after firing have an efficacy period. Maybe super-fine-grain objects? Petri nets are interesting in that they can feedforward state asynchronously.