Engineers, control theorists, and neuroscientists often view the delay imposed by finite signal propagation velocities as a problem that needs to be compensated for or avoided. In this article, we consider the alternative possibility that in some cases, signal delay can be used functionally , that is, as an essential component of a cognitive system. To investigate this idea, we evolve a minimal robot controller to solve a basic stimulus-distinction task. The controller is constrained so that the solution must utilize a delayed recurrent signal. Different from previous evolutionary robotics studies, our controller is modeled using delay differential equations, which (unlike the ordinary differential equations of conventional continuous-time recurrent neural networks) can accurately capture delays in signal propagation. We analyze the evolved controller and its interaction with its environment using classical dynamical systems techniques. The analysis shows what kinds of invariant sets underlie the various successful and unsuccessful performances of the robot, and what kinds of bifurcations produce these invariant sets. In the second phase of our analysis, we turn our attention to the parameter θ , which describes the amount of signal delay included in the model. We show how the delay destabilizes certain attractors that would exist if there were no delay and creates other stable attractors, resulting in an agent that performs well at the target task.

This is a report on the Biological Foundations of Enactivism Workshop, which was held as part of Artificial Life XV. The workshop aimed to revisit enactivism's contributions to biology and to revitalize the discussion of autonomy with the goal of grounding it in quantitative definitions based in observable phenomena. This report summarizes some of the important issues addressed in the workshop's talks and discussions, which include how to identify emergent individuals out of an environmental background, what the roles of autonomy and normativity are in biological theory, how new autonomous agents can spontaneously emerge at the origins of life, and what science can say about subjective experience.