Title :
Evolvable social agents for bacterial systems modeling
Author :
Paton, Ray ; Gregory, Richard ; Vlachos, Costas ; Saunders, Jon ; Wu, Henry
Author_Institution :
BioComput. & Comput. Biol. Res. Group, Univ. of Liverpool, 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.
Keywords :
ecology; evolution (biological); genetics; microorganisms; molecular biophysics; physiological models; adaptive behavioral strategies; bacterial ecologies; bacterial evolution; bacterial systems modeling; coarse grained agent-based model; evolvable social agents; fine-grained model; genes; individual-based modeling; learning classifier systems; proteins; Artificial intelligence; Biological system modeling; Biology computing; Computational biology; Computational modeling; Computer architecture; Computer science; Environmental factors; Evolution (biology); Microorganisms; Adaptation, Physiological; Artificial Intelligence; Bacterial Physiology; Bacterial Proteins; Computer Simulation; Directed Molecular Evolution; Environment; Gene Expression Regulation; Models, Biological; Signal Transduction; Systems Biology;
Journal_Title :
NanoBioscience, IEEE Transactions on
DOI :
10.1109/TNB.2004.833701