  Collective sensing is an emergent phenomenon which enables individuals to
estimate a hidden property of the environment through the observation of social
interactions. Previous work on collective sensing shows that gregarious
individuals obtain an evolutionary advantage by exploiting collective sensing
when competing against solitary individuals. This work addresses the question
of whether collective sensing allows for the emergence of groups from a
population of individuals without predetermined behaviors. It is assumed that
group membership does not lessen competition on the limited resources in the
environment, e.g. groups do not improve foraging efficiency. Experiments are
run in an agent-based evolutionary model of a foraging task, where the fitness
of the agents depends on their foraging strategy. The foraging strategy of
agents is determined by a neural network, which does not require explicit
modeling of the environment and of the interactions between agents. Experiments
demonstrate that gregarious behavior is not the evolutionary-fittest strategy
if resources are abundant, thus invalidating previous findings in a specific
region of the parameter space. In other words, resource scarcity makes
gregarious behavior so valuable as to make up for the increased competition
over the few available resources. Furthermore, it is shown that a population of
solitary agents can evolve gregarious behavior in response to a sudden scarcity
of resources, thus individuating a possible mechanism that leads to gregarious
behavior in nature. The evolutionary process operates on the whole parameter
space of the neural networks, hence these behaviors are selected among an
unconstrained set of behavioral models.
