Insect societies as complex adaptive systems
How does a colony's complex behavior emerge from the interactions of colony members, without direction from a well-informed central controller? Insect societies build complex nests, allocate labor, and adaptively choose among food sources or nest sites, even though each worker has only limited, local information about the problem at hand. This emergence of order at one scale from purely local interactions at a lower scale is a general theme of modern biology, seen also in the interactions of genetic networks to guide development, or of neural networks to generate cognition. It can be difficult to see the links between individual and collective properties, because of the number and diversity of sub-units and the non-linearity of their interactions. Meeting this challenge requires a combination of empirical study with mathematical and computational analysis. This is the approach we use to study collective decision-making by insect societies.
