  Communication and coordination play a major role in the ability of bacterial
cells to adapt to ever changing environments and conditions. Recent work has
shown that such coordination underlies several aspects of bacterial responses
including their ability to develop antibiotic resistance. Here we develop a new
distributed gradient descent method that helps explain how bacterial cells
collectively search for food in harsh environments using extremely limited
communication and computational complexity. This method can also be used for
computational tasks when agents are facing similarly restricted conditions. We
formalize the communication and computation assumptions required for successful
coordination and prove that the method we propose leads to convergence even
when using a dynamically changing interaction network. The proposed method
improves upon prior models suggested for bacterial foraging despite making
fewer assumptions. Simulation studies and analysis of experimental data
illustrate the ability of the method to explain and further predict several
aspects of bacterial swarm food search.
