Introduction

The natural world is an extremely complicated place of myriad interactions – some obvious, some hidden – but all of critical importance if one is to understand its workings. Information must be processed, sorted, ignored or acted upon by all creatures, even though the levels of processing ability vary across species. Scientists, although well aware of these complexities and eager to make sense of them, often begin by reducing interactions to their simplest form, under the assumption that one can gain an understanding of more complex issues by first gaining full knowledge of the simplest. Consequently, in most scientific endeavours, initial studies examine the effect of a single stimulus on an entity: in physics, how light waves interact with a single atom, or how two atoms might interact; in child psychology, the reaction of an infant to a caretaker's smile or to a novel toy; in animal behaviour laboratories, the effect of a shock on the behaviour of a rat's movement in a simple laboratory maze or the effect of a tape loop of song on a bird in a sound isolation box. In each instance, however, the data obtained provide only a small glimmer of the complexity that exists in the real world, and in many cases inferences drawn from data in such experiments truly explain only the specific laboratory situation being studied. To expand to a larger system and a broader base often requires – and triggers – the development of more sophisticated tools, be they mathematical theories (e.g. the Nash equilibrium), more powerful computers for handling data or more sophisticated equipment for gathering data (e.g. complex recording arrays).