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

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

Abstract

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.

Citation

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: https://doi.org/10.1109/UKCI.2013.6651281

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 13th UK workshop on computational intelligence (UKCI 2013)
• 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)
• Peer Reviewed: Peer Reviewed
• Article Number: 6651281
• Pages: 8-15
• Series Title: Proceedings of the UK workshop on computational intelligence
• ISBN: 9781479915682
• DOI: https://doi.org/10.1109/UKCI.2013.6651281
• Keywords: Artificial reaction networks; Artificial chemistry; Swarm agents
• Public URL: http://hdl.handle.net/10059/910
• Contract Date: Dec 16, 2013