QSMM
An adaptive state model development framework.
...A basic building block for supporting state models of finite automatons is adaptive probabilistic mapping, which for an argument from its domain returns more often results that maximize or minimize values of one or more objective functions. Finite automatons can be represented by assembler programs with user-defined instructions that perform effective work. To assist in the learning of a finite automaton, a template for its state model can be provided as an assembler program with probabilistic jump instructions.
The operating principle behind the framework resembles the Boltzmann machine.