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Locating the source of an advected chemical signal is a common challengefacing many living organisms. When the advecting medium is characterized byeither high Reynolds number or high Peclet number the task becomes highlynon-trivial due to the generation of heterogenous, dynamically changingfilamental concentrations which do not decrease monotonically with distance tothe source. Defining search strategies which are effective in theseenvironments has important implications for the understanding of animalbehavior and for the design of biologically inspired technology. Here wepresent a strategy which is able to solve this task without the higherintelligence required to assess spatial gradient direction, measure thediffusive properties of the flow field or perform complex calculations. Insteadour method is based on the collective behavior of autonomous individualsfollowing simple social interaction rules which are modified according to thelocal conditions they are experiencing. Through these context-dependentinteractions the group is able to locate the source of a chemical signal and indoing so displays an awareness of the environment not present at the individuallevel. Our model demonstrates the ability of decentralized informationprocessing systems to solve real world problems and also illustrates analternative pathway to the evolution of higher cognitive capacity via theemergent, group level intelligence which can result from local interactions.

Context-dependent interaction leads to emergent search behavior in social aggregates