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Center for Nonlinear Studies |
Chemotactic bacteria lack a sense of position and their motion is perturbed by thermal noise, yet guided by the local gradient in nutrient concentration they can find its source. Macroscopic searchers, such as animals sensing odors in air or water, detect them only intermittently as patches of odor sweep by, carried by winds and currents. Because of randomness of the advection and mixing processes, local gradients of odor intensity do not point to the source and the searcher must devise a strategy of movement based upon sporadic cues and partial information. We shall discuss a search algorithm, ``infotaxis'', designed to work under such conditions, based on the idea that the rate of acquisition of information on source location can play the same role as concentration in chemotaxis. The proposed search algorithm is relevant to the design of sniffers, olfactory robots with applications to detection of chemical leaks and explosives. The general idea of infotaxis can be applied more broadly in the context of searching with sparse information and provides a framework for quantitative understanding of the balance between the competing ``exploration" and ``exploitation" requirements in learning processes.
Host: Misha Chertkov (T-13/LANL)