Evolvable social agents for bacterial systems modeling.

Ray Paton; Richard Gregory; Costas Vlachos; Jon Saunders; Henry Wu

doi:10.1109/tnb.2004.833701

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Evolvable social agents for bacterial systems modeling.

Ray Paton·Richard Gregory·Costas Vlachos·Jon Saunders·Henry Wu

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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.

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Adaptation, Physiological Artificial Intelligence Bacterial Physiological Phenomena Bacterial Proteins Computer Simulation Directed Molecular Evolution Environment Gene Expression Regulation Models, Biological Signal Transduction Systems Biology Journal Article Research Support, Non-U.S. Gov't

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Ray Paton, Richard Gregory, Costas Vlachos, Jon Saunders, Henry Wu. 2004. Evolvable social agents for bacterial systems modeling.. https://doi.org/10.1109/tnb.2004.833701

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