Abstract
Evolvable Hardware (EHW) has been proposed as a new
method for designing systems for complex real-world
applications. However, so far, only relatively simple
systems have been shown to be evolvable. In this paper,
it is proposed that concepts from biology should be
applied to EHW techniques to make EHW more applicable
to solving complex problems. One such concept has led
to the increased complexity scheme presented, where a
system is evolved by evolving smaller sub-systems.
Experiments with two different tasks illustrate that
inclusion of this scheme substantially reduces the
number of generations required for evolution. Further,
for the prosthesis control task, the best performance
is obtained by the novel approach. The best circuit
evolved performs better than the best trained neural
network.
Users
Please
log in to take part in the discussion (add own reviews or comments).