GP+ echo+ subsumption= improved problem solving

Real-time, adaptive control is a difficult problemthat can be addressed by EC architectures. We
are interested in incorporating into an EC
architecture some of the features that Holland’s
Echo architecture presents. Echo has been used
to model everything from cultures to financial
markets. However, the typical application of
Echo is a simulation to observe the dynamics of
the modeled elements such as found in control
problems. We show in this paper that some
aspects of Echo can be incorporated into Genetic
Programming to solve control problems. The
paper discusses EAGP (Echo Augmented
Genetic Programming), a modified GP
architecture that uses aspects of Echo, and
subsumption. We demonstrate the usefulness of
EAGP on a robot navigation problem