Controlling Complex Dynamics with Artificial Biochemical Networks

TY - JOUR

T1 - Controlling Complex Dynamics with Artificial Biochemical Networks

AU - Lones, Michael A.

AU - Tyrrell, Andy M.

AU - Stepney, Susan

AU - Caves, Leo S.

PY - 2010/4

Y1 - 2010/4

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.

KW - SYSTEMS

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

M3 - Article

SN - 0302-9743

VL - 6021

SP - 159

EP - 170

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

ER -