Benchmark

[Jerry Feldman]

 I suggest the connectionist learning of Finite State Automata (FSA)
as an interesting benchmark. For example, people compute the parity
of a long binary string by an algorithm equivalent to a 2-state FSA.
Sara Porat and I have a constructive proof that FSA learning can be
done from a complete, lexicographically ordered sample so that might
be a reasonable subcase to consider. It is known that the general 
case is NP complete, i.e. very hard. I dont much like the way our
network functions and most of you would hate it, so I don't suggest
starting with our paper. Should anyone care, I could expound on why
the FSA learning problem is an important test of learning models.