Researchers in the field of biocomputing have, for
many years, successfully "harvested and exploited"
the natural world for inspiration in developing systems
that are robust, adaptable and capable of generating
novel and even "creative" solutions to
human-defined problems. However, in this position paper
we argue that the time has now come for a reassessment
of how we exploit biology to generate new computational
systems. Previous solutions (the "first generation"
of biocomputing techniques), whilst reasonably
effective, are crude analogues of actual biological
systems. We believe that a new, inherently
inter-disciplinary approach is needed for the
development of the emerging "second generation" of
bio-inspired methods. This new modus operandi will
require much closer interaction between the engineering
and life sciences communities, as well as a
bidirectional flow of concepts, applications and
expertise. We support our argument by examining, in
this new light, three existing areas of biocomputing
(genetic programming, artificial immune systems and
evolvable hardware), as well as an emerging area
(natural genetic engineering) which may provide useful
pointers as to the way forward.
%0 Generic
%1 oai:arXiv.org:cs/0512071
%A Timmis, Jon
%A Amos, Martyn
%A Banzhaf, Wolfgang
%A Tyrrell, Andy
%D 2005
%K AIS, Artificial Computing EHW, Evolutionary Intelligence; Neural algorithms, and genetic programming,
%T ``Going back to our roots'': second generation
biocomputing
%U http://arxiv.org/abs/cs/0512071
%X Researchers in the field of biocomputing have, for
many years, successfully "harvested and exploited"
the natural world for inspiration in developing systems
that are robust, adaptable and capable of generating
novel and even "creative" solutions to
human-defined problems. However, in this position paper
we argue that the time has now come for a reassessment
of how we exploit biology to generate new computational
systems. Previous solutions (the "first generation"
of biocomputing techniques), whilst reasonably
effective, are crude analogues of actual biological
systems. We believe that a new, inherently
inter-disciplinary approach is needed for the
development of the emerging "second generation" of
bio-inspired methods. This new modus operandi will
require much closer interaction between the engineering
and life sciences communities, as well as a
bidirectional flow of concepts, applications and
expertise. We support our argument by examining, in
this new light, three existing areas of biocomputing
(genetic programming, artificial immune systems and
evolvable hardware), as well as an emerging area
(natural genetic engineering) which may provide useful
pointers as to the way forward.
@misc{oai:arXiv.org:cs/0512071,
abstract = {Researchers in the field of biocomputing have, for
many years, successfully {"}harvested and exploited{"}
the natural world for inspiration in developing systems
that are robust, adaptable and capable of generating
novel and even {"}creative{"} solutions to
human-defined problems. However, in this position paper
we argue that the time has now come for a reassessment
of how we exploit biology to generate new computational
systems. Previous solutions (the {"}first generation{"}
of biocomputing techniques), whilst reasonably
effective, are crude analogues of actual biological
systems. We believe that a new, inherently
inter-disciplinary approach is needed for the
development of the emerging {"}second generation{"} of
bio-inspired methods. This new modus operandi will
require much closer interaction between the engineering
and life sciences communities, as well as a
bidirectional flow of concepts, applications and
expertise. We support our argument by examining, in
this new light, three existing areas of biocomputing
(genetic programming, artificial immune systems and
evolvable hardware), as well as an emerging area
(natural genetic engineering) which may provide useful
pointers as to the way forward.},
added-at = {2008-06-19T17:46:40.000+0200},
author = {Timmis, Jon and Amos, Martyn and Banzhaf, Wolfgang and Tyrrell, Andy},
bibsource = {OAI-PMH server at arXiv.org},
biburl = {https://www.bibsonomy.org/bibtex/2969dfd941448a80c33cd685cce309e99/brazovayeye},
howpublished = {arXiv},
interhash = {4720969c770365412b4d11bee5d186a1},
intrahash = {969dfd941448a80c33cd685cce309e99},
keywords = {AIS, Artificial Computing EHW, Evolutionary Intelligence; Neural algorithms, and genetic programming,},
month = {December~16},
note = {Submitted to the International Journal of
Unconventional Computing},
oai = {oai:arXiv.org:cs/0512071},
size = {36 pages},
timestamp = {2008-06-19T17:53:09.000+0200},
title = {``Going back to our roots'': second generation
biocomputing},
url = {http://arxiv.org/abs/cs/0512071},
year = 2005
}