Evolution provides a creative fount of complex and subtle adaptations that often surprise the scientists who discover them. However, the creativity of evolution is not limited to the natural world: Artificial organisms evolving in computational environments have also elicited surprise and wonder from the researchers studying them. The process of evolution is an algorithmic process that transcends the substrate in which it occurs. Indeed, many researchers in the field of digital evolution can provide examples of how their evolving algorithms and organisms have creatively subverted their expectations or intentions, exposed unrecognized bugs in their code, produced unexpectedly adaptations, or engaged in behaviors and outcomes, uncannily convergent with ones found in nature. Such stories routinely reveal surprise and creativity by evolution in these digital worlds, but they rarely fit into the standard scientific narrative. Instead they are often treated as mere obstacles to be overcome, rather than results that warrant study in their own right. Bugs are fixed, experiments are refocused, and one-off surprises are collapsed into a single data point. The stories themselves are traded among researchers through oral tradition, but that mode of information transmission is inefficient and prone to error and outright loss. Moreover, the fact that these stories tend to be shared only among practitioners means that many natural scientists do not realize how interesting and lifelike digital organisms are and how natural their evolution can be. To our knowledge, no collection of such anecdotes has been published before. This article is the crowd-sourced product of researchers in the fields of artificial life and evolutionary computation who have provided first-hand accounts of such cases. It thus serves as a written, fact-checked collection of scientifically important and even entertaining stories. In doing so we also present here substantial evidence that the existence and importance of evolutionary surprises extends beyond the natural world, and may indeed be a universal property of all complex evolving systems.

This project focuses on developing a flapping-wing hovering insect using 3D-printed wings and mechanical parts. The use of 3D printing technology has greatly expanded the possibilities for wing design, allowing wing shapes to replicate those of real insects or virtually any other shape. It has also reduced the time of a wing design cycle to a matter of minutes. An ornithopter with a mass of 3.89 g has been constructed using the 3D printing technique and has demonstrated an 85-s passively stable untethered hovering flight. This flight exhibits the functional utility of printed materials for flapping-wing experimentation and ornithopter construction and for understanding the mechanical principles underlying insect flight and control.

The difficulties associated with designing, building, and controlling robots have led their development to a stasis: Applications are limited mostly to repetitive tasks with predefined behavior. Over the last few years we have been trying to address this challenge through an alternative approach: Rather than trying to control an existing machine or create a general-purpose robot, we propose that both the morphology and the controller should evolve at the same time. This process can lead to the automatic design of special-purpose mechanisms and controllers for specific short-term objectives. Here we provide a brief review of three generations of our recent research, which underlies the robots shown on the cover of this issue: Automatically designed static structures, automatically designed and manufactured dynamic electromechanical systems, and modular robots automatically designed through a generative DNA-like encoding.