Controlling Complex Dynamics with Artificial Biochemical Networks

TY - CONF

T1 - Controlling Complex Dynamics with Artificial Biochemical Networks

AU - Lones, Michael A.

AU - Tyrrell, Andy M.

AU - Stepney, Susan

AU - Caves, Leo S. D.

PY - 2010

Y1 - 2010

N2 - Artificial biochemical networks (ABNs) are computational models inspired by the biochemical networks which underlie the cellular activities of biological organisms. This paper shows how evolved ABNs may be used to control chaotic dynamics in both discrete and continuous dynamical systems, illustrating that ABNs can be used to represent complex computational behaviours within evolutionary algorithms. Our results also show that performance is sensitive to model choice, and suggest that conservation laws play an important role in guiding search.

AB - Artificial biochemical networks (ABNs) are computational models inspired by the biochemical networks which underlie the cellular activities of biological organisms. This paper shows how evolved ABNs may be used to control chaotic dynamics in both discrete and continuous dynamical systems, illustrating that ABNs can be used to represent complex computational behaviours within evolutionary algorithms. Our results also show that performance is sensitive to model choice, and suggest that conservation laws play an important role in guiding search.

UR - http://www.scopus.com/inward/record.url?scp=77952298333&partnerID=8YFLogxK

M3 - Paper

SP - 159

EP - 170

T2 - European Conference on Genetic Programming, EuroGP 2010

Y2 - 1 April 2010

ER -