Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-12148-7_14 | EuroGP |
Keywords | Field | DocType |
chaotic dynamic,artificial biochemical network,biochemical network,biological organism,conservation law,continuous dynamical system,cellular activity,evolutionary algorithm,complex dynamic,computational model,complex computational behaviour,dynamic system,computer model,complex dynamics | Boolean network,Complex dynamics,Evolutionary algorithm,Computer science,Metabolic network,Lorenz system,Computational model,Dynamical systems theory,Artificial intelligence,Chaotic | Conference |
Volume | ISSN | ISBN |
6021 | 0302-9743 | 3-642-12147-0 |
Citations | PageRank | References |
17 | 1.51 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michael A. Lones | 1 | 168 | 20.42 |
| Andy M. Tyrrell | 2 | 629 | 73.61 |
| Susan Stepney | 3 | 813 | 113.21 |
| Leo S. Caves | 4 | 514 | 43.16 |