Data from: Exploring the Importance of Stochasticity to Hybrid Equilibria in a Discrete Signaling Game

Communication via evolved signals is ubiquitous (both within and between
species) in the natural world. However, how honest we should expect
signals to be remains an open question. Hybrid equilibria are a form of
equilibria predicted by discrete signaling games in which signalers are
sometimes dishonest and signals do not completely reliably convey
information on signaler quality. While these equilibria have been
theoretically demonstrated in several signaling games, their dynamics in a
stochastic simulation of evolutionary trajectories (that include
representation of the inherent noise expected in evolution in the natural
world) have not previously been studied. In this paper, we present an
agent-based simulation of a discrete signaling game which exhibits hybrid
equilibria. We find that while hybrid equilibria are evolutionarily
attractive where they exist, populations exhibit vairable and often
drastic oscillating behavior around the predicted equilibrium values. We
discuss how these dynamics might offer valuable opportunity for detecting
hybrid equilibria in natural populations.