A Bacterial-Based Algorithm to Simulate Complex Adaptative Systems

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ISSN: 0302-9743
ISBN: 978-3-319-08863-1
ISBN: 978-3-319-08864-8 (online)
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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.
Paper presented at the 13th International Conference on Simulation of Adaptive Behavior which took place at Castellón, Spain in 2014, July 22-25.
Complexity, Artificial Society, Bacterial-based Algorithms, P2P Society, Complex Adaptive Systems, CAS
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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.