THE EVOLUTION OF EXPLOITATION AND HONESTY IN ANIMAL COMMUNICATION - AMODEL USING ARTIFICIAL NEURAL NETWORKS

Conflicts of interest arise between signaller and receiver in most kin ds of biological communication. Some authors have argued that this con flict is likely to give rise to deceit and exploitation, as receivers lag behind in the coevolutionary 'arms race' with signallers. Others h ave argued that such manipulation is likely to be short-lived and that receivers can avoid being deceived by paying attention to signals tha t are costly and hence 'unfakeable'. These two views have been hard to reconcile. Here, we present results from simulations of signal evolut ion using artificial neural networks, which demonstrate that honesty c an coexist with a degree of exploitation. Signal cost ensures that rec eivers are able to obtain some honest information, but is unable to pr event exploitative signalling strategies from gaining short-term benef its. Although any one receiver bias that is open to exploitation will subsist for only a short period of time once signallers begin to take advantage of it, new preferences of this kind are constantly regenerat ed through selection and random drift. Hidden preferences and sensory exploitation are thus likely to have an enduring influence on the evol ution of honest, costly signals. At the same time, honesty and cost ar e prerequisites for the evolution of exploitation. When signalling is cost-free, selection cannot act to maintain honesty, and receivers rap idly evolve to ignore signals. This leads to a reduction in the extent of hidden preference, and a consequent loss of potential for exploita tion.