Letter

Nature 445, 406-409 (25 January 2007) | doi:10.1038/nature05464; Received 1 May 2006; Accepted 14 November 2006

'Infotaxis' as a strategy for searching without gradients

Massimo Vergassola1, Emmanuel Villermaux2 & Boris I. Shraiman3

  1. CNRS URA 2171, Institut Pasteur, "In Silico Genetics", 75724 Paris Cedex 15, France
  2. Université Aix Marseille 1, IRPHE, Technopole Chateau Gombert, F-13384 Marseille, France
  3. Kavli Institute for Theoretical Physics, University of California, Santa Barbara, California 93106, USA

Correspondence to: Boris I. Shraiman3 Correspondence and requests for materials should be addressed to B.I.S. (Email: shraiman@kitp.ucsb.edu).

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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