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.
Description
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
%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
}