Biomimicry of bacterial foraging for distributed optimization and control

We explain the biology and physics underlying the chemotactic (foraging) behavior of E. coli bacteria. We explain a variety of bacterial swarming and social foraging behaviors and discuss the control system on the E. coli that dictates how foraging should proceed. Next, a computer program that emulates the distributed optimization process represented by the activity of social bacterial foraging is presented. To illustrate its operation, we apply it to a simple multiple-extremum function minimization problem and briefly discuss its relationship to some existing optimization algorithms. The article closes with a brief discussion on the potential uses of biomimicry of social foraging to develop adaptive controllers and cooperative control strategies for autonomous vehicles. For this, we provide some basic ideas and invite the reader to explore the concepts further.

[1]  J P Armitage,et al.  Bacterial tactic responses. , 1999, Advances in microbial physiology.

[2]  Laurent Keller,et al.  Ant-like task allocation and recruitment in cooperative robots , 2000, Nature.

[3]  H. Van Dyke Parunak,et al.  Multiple Pheromones for Improved Guidance , 2000 .

[4]  Howard C. Berg,et al.  Rapid rotation of flagellar bundles in swimming bacteria , 1987, Nature.

[5]  D J DeRosier,et al.  The Turn of the Screw: The Bacterial Flagellar Motor , 1998, Cell.

[6]  James A. Shapiro,et al.  BACTERIA AS MULTICELLULAR ORGANISMS , 1988 .

[7]  H. Berg,et al.  Chemotaxis in Escherichia coli analysed by Three-dimensional Tracking , 1972, Nature.

[8]  H. Berg,et al.  Spatio-temporal patterns generated by Salmonella typhimurium. , 1995, Biophysical journal.

[9]  R. Losick,et al.  Why and how bacteria communicate. , 1997, Scientific American.

[10]  H. Berg,et al.  Temporal comparisons in bacterial chemotaxis. , 1986, Proceedings of the National Academy of Sciences of the United States of America.

[11]  Kevin M. Passino,et al.  Genetic Adaptive and Supervisory Control , 2000 .

[12]  J. Doyle,et al.  Robust perfect adaptation in bacterial chemotaxis through integral feedback control. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[13]  Kevin M. Passino,et al.  Genetic adaptive identification and control , 1999 .

[14]  Angela Stevens,et al.  A Stochastic Cellular Automaton Modeling Gliding and Aggregation of Myxobacteria , 2000, SIAM J. Appl. Math..

[15]  Angela Stevens,et al.  Simulations of the Gliding Behavior and Aggregation of Myxobacteria , 1990 .

[16]  H. Berg,et al.  Complex patterns formed by motile cells of Escherichia coli , 1991, Nature.

[17]  M. Eisenbach,et al.  Tar-dependent and -independent pattern formation by Salmonella typhimurium , 1995, Journal of bacteriology.

[18]  H. Berg,et al.  Dynamics of formation of symmetrical patterns by chemotactic bacteria , 1995, Nature.

[19]  H. Berg.  Motile Behavior of Bacteria , 2000 .

[20]  J. Spall,et al.  Some theoretical comparisons of stochastic optimization approaches , 2000, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).

[21]  Guy Albert Dumont,et al.  System identification and control using genetic algorithms , 1992, IEEE Trans. Syst. Man Cybern..