Evolvable social agents for bacterial systems modeling
Related Experiment Video
Updated: Aug 21, 2026

Time-lapse Imaging of Bacterial Swarms and the Collective Stress Response
Published on: May 23, 2020
Ray Paton1, Richard Gregory, Costas Vlachos
1BioComputing and Computational Biology Research Group, Department of Computer Science, University of Liverpool, Liverpool L69 7ZF, UK.
Abstract:
We present two approaches to the individual-based modeling (IbM) of bacterial ecologies and evolution using computational tools. The IbM approach is introduced, and its important complementary role to biosystems modeling is discussed. A fine-grained model of bacterial evolution is then presented that is based on networks of interactivity between computational objects representing genes and proteins. This is followed by a coarser grained agent-based model, which is designed to explore the evolvability of adaptive behavioral strategies in artificial bacteria represented by learning classifier systems. The structure and implementation of the two proposed individual-based bacterial models are discussed, and some results from simulation experiments are presented, illustrating their adaptive properties.
Related Concept Videos
Evolutionary Processes in Microbes
Coordination of Gene Expression Processes in Bacteria
Evolution of New Traits in Microbes
Bacterial Signaling
Regulation of Bacterial Virulence
Gene Regulation in Microbial Communities: Quorum Sensing

