Benchmark

[Jerry Feldman]

Geoff,

  I thought you'd never ask. Finite State Automata (FSA) are the most
primitive infitary systems. Almost all connectionist learning has involved
only input/output maps, a very restricted form of computation. Tasks of
psychological or engineering interest involve multiple step calculcations
and FSA are the simplest of these. There is also lots of literature on
FSA and the learning thereof and the generalization issue is clear.

  The benchmark task is to exhibit an initial network and learning rule that
will converge(approximately, if you'd like) to a minimal FSA from ANY large
sample generated by an FSA. There are several encodings possible including
one-unit/one-state, Jordan's state vector or even the state of the whole
network. As I said in response to Fahlman, a solution in any form would be
fine. 

Jerry