Modeling, simulation, control and optimization paradigms for E.coli bacteria

This paper examines possible mechanisms of control and decision-making in Escherichia coli (E.coli) bacteria. In particular, by making use available experimental data, we illustrate that many phenomena can be studied applying viable optimization paradigms. The simulation and data-intensive analysis performed illustrate that the proposed methods suitable to coherently examine complex behavior of biosystems. In particular, bacteria perform the following synergetic functions: intelligence, learning, adaptation, analysis, sensing, decision-making, planning, coordination, etc. For example, complex swarming patterns are observed. The ultimate objective was to develop mathematical foundations and apply the results for complex multi-agent systems that require adaptive distributed control in highly dynamic adverse environments.