PCs, being generally more effective, have replaced typewriters in our everyday lives; but, at the same time, introduce a lot of complexity. As a result, many of us are left wondering at PCs as if they were mysterious ghosts in the machine : entities with powers we cannot explain or control, almost supernatural. We analyze this increase in technological complexity at two levels in our society, one economic and one scientific, and we discuss how the field of Artificial Life (ALife) can attempt to rescue our society. At the economic level, there is evidence that computers, being so much more complex, slow labor productivity down rather than increasing it (e.g., maintenance, malware, distractions). Computers are also the subject of debate surrounding technological unemployment. We advocate for ALife to focus on developments that, like the xenobots, are minimally intrusive to our everyday work and occupy unfilled economic niches. At the scientific level, the surge in Artificial Intelligence (AI) has begotten a plethora of complex algorithms that mimic the cognition happening in animal brains: they are usually not interpretable and even their creators struggle to make sense of them. We advocate for ALife to focus more on basal forms of cognition— cognition that requires as little “brain” as possible, potentially none; algorithms that think through their bodies, stripped of any superfluous complexity, just like typewriters.

Our modern world is teeming with non-biological agents, whose growing complexity brings them so close to living beings that they can be cataloged as artificial creatures, i.e., a form of Artificial Life (ALife). Ranging from disembodied intelligent agents to robots of conspicuous dimensions, all these artifacts are united by the fact that they are designed, built, and possibly trained by humans taking inspiration from natural elements. Hence, humans play a fundamental role in relation to ALife, both as creators and as final users, which calls attention to the need of studying the mutual influence of human and artificial life. Here we attempt an experimental investigation of the reciprocal effects of the human-ALife interaction. To this extent, we design an artificial world populated by life-like creatures, and resort to open-ended evolution to foster the creatures adaptation. We allow bidirectional communication between the system and humans, who can observe the artificial world and voluntarily choose to perform positive or negative actions towards the creatures populating it; those actions may have a short- or long-term impact on the artificial creatures. Our experimental results show that the creatures are capable of evolving under the influence of humans, even though the impact of the interaction remains uncertain. In addition, we find that ALife gives rise to disparate feelings in humans who interact with it, who are not always aware of the importance of their conduct.

Biological agents possess bodies that are mostly of soft tissues. Researchers have resorted to soft bodies to investigate Artificial Life (ALife)-related questions; similarly, a new era of soft-bodied robots has just begun. Nevertheless, because of their infinite degrees of freedom, soft bodies pose unique challenges in terms of simulation, control, and optimization. Here we propose a novel soft-bodied agents formalism, namely Pressure-based Soft Agents (PSAs): they are bodies of gas enveloped by a chain of springs and masses, with pressure pushing on the masses from inside the body. Pressure endows the agents with structure, while springs and masses simulate softness and allow the agents to assume a large gamut of shapes. Actuation takes place by changing the length of springs or modulating global pressure. We optimize the controller of PSAs for a locomotion task on hilly terrain and an escape task from a cage; the latter is particularly suitable for soft-bodied agents, as it requires the agent to contort itself to squeeze through a small aperture. Our results suggest that PSAs are indeed effective at those tasks and that controlling pressure is fundamental for shape-changing. Looking forward, we envision PSAs to play a role in the modeling of soft-bodied agents, including soft robots and biological cells. 1