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Combining biochemical network motifs within an ARN-agent control system.

Gerrard, Claire E.; McCall, John; Macleod, Christopher; Coghill, George M.


Claire E. Gerrard

Christopher Macleod

George M. Coghill


Yaochu Jin

Spencer Angus Thomas


The Artificial Reaction Network (ARN) is an Artificial Chemistry representation inspired by cell signaling networks. The ARN has previously been applied to the simulation of the chemotaxis pathway of Escherichia coli and to the control of limbed robots. In this paper we discuss the design of an ARN control system composed of a combination of network motifs found in actual biochemical networks. Using this control system we create multiple cell-like autonomous agents capable of coordinating all aspects of their behavior, recognizing environmental patterns and communicating with other agent's stigmergically. The agents are applied to simulate two phases of the life cycle of Dictyostelium discoideum: vegetative and aggregation phase including the transition. The results of the simulation show that the ARN is well suited for construction of biochemical regulatory networks. Furthermore, it is a powerful tool for modeling multi agent systems such as a population of amoebae or bacterial colony.


GERRARD, C.E., MCCALL, J., MACLEOD, C. and COGHILL, G.M. 2013. Combining biochemical network motifs within an ARN-agent control system. In Jin, Y. and Thomas, S.A. (eds.) Proceedings of the 13th UK workshop on computational intelligence (UKCI 2013), 9-11 September 2013, Guildford, UK. New York: IEEE [online], article number 6651281, pages 8-15. Available from:

Conference Name 13th UK workshop on computational intelligence (UKCI 2013)
Conference Location Guildford, UK
Start Date Sep 9, 2013
End Date Sep 11, 2013
Acceptance Date Sep 11, 2013
Online Publication Date Sep 11, 2013
Publication Date Oct 31, 2013
Deposit Date Dec 16, 2013
Publicly Available Date Dec 16, 2013
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Article Number 6651281
Pages 8-15
Series Title Proceedings of the UK workshop on computational intelligence
ISBN 9781479915682
Keywords Artificial reaction networks; Artificial chemistry; Swarm agents
Public URL


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