Biomimicry of bacterial foraging for distributed optimization and control

TLDR

The paper investigates how E. coli chemotaxis and social foraging can inspire distributed optimization and adaptive control for autonomous vehicles. The authors model bacterial foraging as a distributed optimization algorithm, implement it in a computer program, and apply it to a simple multiple‑extremum minimization problem to compare with existing methods.

Abstract

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.