Abstract
FIFTH, a new stack-based genetic programming language,
efficiently expresses solutions to a large class of
feature recognition problems. This problem class
includes mining time-series data, classification of
multivariate data, image segmentation, and digital
signal processing (DSP). FIFTH is based on FORTH
principles. Key features of FIFTH are a single data
stack for all data types and support for vectors and
matrices as single stack elements. We demonstrate that
the language characteristics allow simple and elegant
representation of signal processing algorithms while
maintaining the rules necessary to automatically evolve
stack correct and control flow correct programs. FIFTH
supports all essential program architecture constructs
such as automatically defined functions, loops,
branches, and variable storage. An XML configuration
file provides easy selection from a rich set of
operators, including domain specific functions such as
the Fourier transform (FFT). The fully-distributed
FIFTH environment (GPE5) uses CORBA for its underlying
process communication.
Users
Please
log in to take part in the discussion (add own reviews or comments).