Evolvable social agents for bacterial systems modeling

Authored by C Vlachos, R Gregory

Date Published: 2004-09

DOI: 10.1109/tnb.2004.833701

Sponsors: No sponsors listed

Platforms: No platforms listed

Model Documentation: Other Narrative

Model Code URLs: Model code not found

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.

Tags

artificial ecologies network-based models rule-based models Adaptive Behavior individual-based modeling (IbM) virtual bacteria Cell