  From an enactive approach, some previous studies have demonstrated that
social interaction plays a fundamental role in the dynamics of neural and
behavioral complexity of embodied agents. In particular, it has been shown that
agents with a limited internal structure (2-neuron brains) that evolve in
interaction can overcome this limitation and exhibit chaotic neural activity,
typically associated with more complex dynamical systems (at least
3-dimensional). In the present paper we make two contributions to this line of
work. First, we propose a conceptual distinction in levels of coupling between
agents that could have an effect on neural and behavioral complexity. Second,
we test the generalizability of previous results by testing agents with richer
internal structure and evolving them in a richer, yet non-social, environment.
We demonstrate that such agents can achieve levels of complexity comparable to
agents that evolve in interactive settings. We discuss the significance of this
result for the study of interaction.
