%0 Generic %1 gonzalezrodriguez2016bacterialbased %A González Rodríguez, Diego %A Hernández Carrión, José Rodolfo %D 2016 %I Springer %K biology heterogeneity %T A Bacterial-Based Algorithm to Simulate Complex Adaptative Systems %U http://e-archivo.uc3m.es/handle/10016/22371 %X 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.

@misc{gonzalezrodriguez2016bacterialbased, 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.}, added-at = {2016-03-10T18:20:10.000+0100}, author = {González Rodríguez, Diego and Hernández Carrión, José Rodolfo}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2ea39a99398d0267efeadb7a437b7af4b/mariusoei}, description = {A Bacterial-Based Algorithm to Simulate Complex Adaptative Systems}, id = {From Animals to Animats 13: 13th International Conference on Simulation of Adaptative Behaviour, SAB 2014, Castellón, Spain, July 22-25, 2014. Proceedings}, interhash = {deea3ccb471c3db5cbd399599f3c8b2f}, intrahash = {ea39a99398d0267efeadb7a437b7af4b}, keywords = {biology heterogeneity}, publisher = {Springer}, timestamp = {2016-03-10T17:20:10.000+0100}, title = {A Bacterial-Based Algorithm to Simulate Complex Adaptative Systems}, type = {conferenceObject, acceptedVersion}, url = {http://e-archivo.uc3m.es/handle/10016/22371}, year = 2016 }