  The purpose of this paper is to present an algorithm for inferring
nondeterministic functional transducers. It has a lot in common with other well
known algorithms such has RPNI and OSTIA. Indeed we will argue that this
algorithm is a generalisation of both of them. Functional transducers are all
those nondeterministic transducers whose regular relation is a function.
Epsilon transitions as well as subsequential output can be erased for such
machines, with the exception of output for empty string being lost. Learning
partial functional transducers from negative examples is equivalent to learning
total from positive-only data.
