  Locating the source of an advected chemical signal is a common challenge
facing many living organisms. When the advecting medium is characterized by
either high Reynolds number or high Peclet number the task becomes highly
non-trivial due to the generation of heterogenous, dynamically changing
filamental concentrations which do not decrease monotonically with distance to
the source. Defining search strategies which are effective in these
environments has important implications for the understanding of animal
behavior and for the design of biologically inspired technology. Here we
present a strategy which is able to solve this task without the higher
intelligence required to assess spatial gradient direction, measure the
diffusive properties of the flow field or perform complex calculations. Instead
our method is based on the collective behavior of autonomous individuals
following simple social interaction rules which are modified according to the
local conditions they are experiencing. Through these context-dependent
interactions the group is able to locate the source of a chemical signal and in
doing so displays an awareness of the environment not present at the individual
level. Our model demonstrates the ability of decentralized information
processing systems to solve real world problems and also illustrates an
alternative pathway to the evolution of higher cognitive capacity via the
emergent, group level intelligence which can result from local interactions.
