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dc.contributor.authorGerrard, Claire E.
dc.contributor.authorMcCall, John
dc.contributor.authorMacleod, Christopher
dc.contributor.authorCoghill, George M.
dc.date.accessioned2013-12-16T09:50:01Z
dc.date.available2013-12-16T09:50:01Z
dc.date.issued2013-09
dc.identifier.citationGERRARD, C. E., MCCALL, J., MACLEOD, C. and COGHILL, G. M., 2013. Combining biochemical network motifs within an ARN-agent control system. In: Y. JIN and S. A. THOMAS, eds. Proceedings of the 13th UK Workshop on Computational Intelligence (UKCI) 2013 9-11 September 2013. New York: IEEE. pp. 8-15.en
dc.identifier.isbn9781479915668en
dc.identifier.urihttp://hdl.handle.net/10059/910
dc.description.abstractThe 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.en
dc.language.isoenen
dc.publisherIEEEen
dc.relation.ispartof13th UK Workshop on Computational Intelligence (UKCI) 2013en
dc.rights“© © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”en
dc.subjectArtificial Reaction Networksen
dc.subjectArtificial chemistryen
dc.subjectSwarm agentsen
dc.titleCombining biochemical network motifs within an ARN-agent control system.en
dc.typeConference publicationsen
dc.publisher.urihttp://dx.doi.org/10.1109/UKCI.2013.6651281en


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