A Bacterial-Based Algorithm to Simulate Complex Adaptative Systems

e-Archivo Repository

Show simple item record

dc.contributor.author González Rodríguez, Diego
dc.contributor.author Hernández Carrión, José Rodolfo
dc.date.accessioned 2016-02-26T09:03:24Z
dc.date.available 2016-02-26T09:03:24Z
dc.date.issued 2014
dc.identifier.bibliographicCitation González Rodríguez, D., Hernández Carrión, J.R. 2014. A Bacterial-Based Algorithm to Simulate Complex Adaptative Systems. From Animals to Animats 13: 13th International Conference on Simulation of Adaptative Behaviour, SAB 2014, Castellón, Spain, July 22-25, 2014. Proceedings, pp. 250-259.
dc.identifier.isbn 978-3-319-08863-1
dc.identifier.isbn 978-3-319-08864-8 (online)
dc.identifier.issn 0302-9743
dc.identifier.uri http://hdl.handle.net/10016/22371
dc.description Paper presented at the 13th International Conference on Simulation of Adaptive Behavior which took place at Castellón, Spain in 2014, July 22-25.
dc.description.abstract Bacteria have demonstrated an amazing capacity to overcome envi-ronmental changes by collective adaptation through genetic exchanges. Using a distributed communication system and sharing individual strategies, bacteria propagate mutations as innovations that allow them to survive in different envi-ronments. In this paper we present an agent-based model which is inspired by bacterial conjugation of DNA plasmids. In our approach, agents with bounded rationality interact in a common environment guided by local rules, leading to Complex Adaptive Systems that are named 'artificial societies'. We have demonstrated that in a model based on free interactions among autonomous agents, optimal results emerge by incrementing heterogeneity levels and decentralizing communication structures, leading to a global adaptation of the system. This organic approach to model peertopeer dynamics in Complex Adaptive Systems is what we have named ‘bacterial-based algorithms’ because agents exchange strategic information in the same way that bacteria use conjugation and share genome.
dc.format.extent 10
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Springer
dc.relation.ispartof http://hdl.handle.net/10016/22239
dc.relation.ispartofseries Lecture Notes in Computer Sciences (LNCS)
dc.relation.ispartofseries 8575
dc.rights © 2014 Springer
dc.subject.other Complexity
dc.subject.other Artificial Society
dc.subject.other Bacterial-based Algorithms
dc.subject.other P2P Society
dc.subject.other Complex Adaptive Systems
dc.subject.other CAS
dc.title A Bacterial-Based Algorithm to Simulate Complex Adaptative Systems
dc.type conferenceObject
dc.relation.publisherversion http://dx.doi.org/10.1007/978-3-319-08864-8_24
dc.subject.eciencia Biblioteconomía y Documentación
dc.identifier.doi 10.1007/978-3-319-08864-8_24
dc.rights.accessRights openAccess
dc.type.version acceptedVersion
dc.relation.eventdate July 22-25, 2014
dc.relation.eventnumber 13
dc.relation.eventplace Castellón, Spain
dc.relation.eventtitle SAB 2014: 13th International Conference on Simulation of Adaptive Behavior
dc.relation.eventtype proceeding
dc.identifier.publicationfirstpage 250
dc.identifier.publicationlastpage 259
dc.identifier.publicationtitle From Animals to Animats 13: 13th International Conference on Simulation of Adaptative Behaviour, SAB 2014, Castellón, Spain, July 22-25, 2014. Proceedings
 Find Full text

Files in this item

*Click on file's image for preview. (Embargoed files's preview is not supported)


This item appears in the following Collection(s)

Show simple item record