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‘Infotaxis’ as a strategy for searching without gradients


Chemotactic bacteria rely on local concentration gradients to guide them towards the source of a nutrient1. Such local cues pointing towards the location of the source are not always available at macroscopic scales because mixing in a flowing medium breaks up regions of high concentration into random and disconnected patches. Thus, animals sensing odours in air or water detect them only intermittently as patches sweep by on the wind or currents2,3,4,5,6. A macroscopic searcher must devise a strategy of movement based on sporadic cues and partial information. Here we propose a search algorithm, which we call ‘infotaxis’, designed to work under such conditions. Any search process can be thought of as acquisition of information on source location; for infotaxis, information plays a role similar to concentration in chemotaxis. The infotaxis strategy locally maximizes the expected rate of information gain. We demonstrate its efficiency using a computational model of odour plume propagation and experimental data on mixing flows7. Infotactic trajectories feature ‘zigzagging’ and ‘casting’ paths similar to those observed in the flight of moths8. The proposed search algorithm is relevant to the design of olfactory robots9,10,11, but the general idea of infotaxis can be applied more broadly in the context of searching with sparse information.

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Figure 1: Typical infotactic trajectories.
Figure 2: Quantitative characterization of infotaxis searches.
Figure 3: Simulation of infotaxis using mixing flow experimental data7.


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This work was done during the visits of M.V. and E.V. to KITP, and was supported by the ARO. E.V. is a member of the Institut Universitaire de France.

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Correspondence to Boris I. Shraiman.

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Vergassola, M., Villermaux, E. & Shraiman, B. ‘Infotaxis’ as a strategy for searching without gradients. Nature 445, 406–409 (2007).

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