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Applications and design of cooperative multi-agent ARN-based systems.

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


Claire E. Gerrard

Christopher Macleod

George M. Coghill


The Artificial Reaction Network (ARN) is an Artificial Chemistry inspired by Cell Signalling Networks (CSNs). Its purpose is to represent chemical circuitry and to explore the computational properties responsible for generating emergent high-level behaviour. In previous work, the ARN was applied to the simulation of the chemotaxis pathway of E. coli and to the control of quadrupedal robotic gaits. In this paper, the design and application of ARN-based cell-like agents termed Cytobots are explored. Such agents provide a facility to explore the dynamics and emergent properties of multicellular systems. The Cytobot ARN is constructed by combining functional motifs found in real biochemical networks. By instantiating this ARN, multiple Cytobots are created, each of which is capable of recognizing environmental patterns, stigmergic communication with others and controlling its own trajectory. Applications in biological simulation and robotics are investigated by first applying the agents to model the life-cycle phases of the cellular slime mould D. discoideum and then to simulate an oil-spill clean-up operation. The results demonstrate that an ARN based approach provides a powerful tool for modelling multi-agent biological systems and also has application in swarm robotics.


GERRARD, C.E., MCCALL, J., MACLEOD, C. and COGHILL, G.M. 2015. Applications and design of cooperative multi-agent ARN-based systems. Soft computing [online], 19(6), pages 1581-1594. Available from:

Journal Article Type Article
Acceptance Date Jun 21, 2014
Online Publication Date Jun 21, 2014
Publication Date Jun 30, 2015
Deposit Date Jun 11, 2015
Publicly Available Date Jun 11, 2015
Journal Soft computing
Print ISSN 1432-7643
Electronic ISSN 1433-7479
Publisher Springer
Peer Reviewed Peer Reviewed
Volume 19
Issue 6
Pages 1581-1594
Keywords Artificial biochemical network (ABN); Artificial chemistry; Artificial neural network (ANN); Swarm robotics
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