Publication Details
Ubiquity symposium: Evolutionary computation and the processes of life: evolutionary computation in physical world
evolutionary computation, evolvable hardware, computing theory
Evolutionary algorithms (EA) are population-based search algorithms. They have
been applied to solve numerous engineering as well as scientific design and
optimization problems, in many cases outperforming conventional methods or other
search-based methods. Dozens of human-competitive results obtained using EA were
awarded at the annual GECCO Humies competitions. Despite these achievements, the
EA-based problem solving approach has been criticized mainly because of very long
runtimes, insufficient scalability, an inherently stochastic nature and a missing
rigorous theoretical background, especially regarding the convergence analysis.
In order to speed up the EA, particularly the fitness function evaluation,
various accelerators have been proposed utilizing clusters of computers, graphics
processing units (GPUs) or specialized hardware. This contribution to the
Ubiquity Symposium addresses the scenario in which evolutionary design (or
optimization) is carried out on a chip and candidate designs are real physical
entities such as electronic circuits. It will be shown that this approach
exhibits several unique features that are very relevant to the purpose of this
symposium. We will address the question on what it means for a physical system to
be designed evolutionarily and on what kinds of computations such physical
systems perform.
@article{BUT103424,
author="Lukáš {Sekanina}",
title="Ubiquity symposium: Evolutionary computation and the processes of life: evolutionary computation in physical world",
journal="Ubiquity",
year="2013",
volume="2013",
number="2",
pages="1--7",
doi="10.1145/2435197.2435199",
issn="1530-2180",
url="http://ubiquity.acm.org/article.cfm?id=2435199"
}