Can music emerge from a swarm of robots each playing a single note and coordinating its behaviour with the others? We explore this idea by proposing a modular framework for the emergent generation of music, representing a novel intersection between robotics and artistic creation. We move beyond the works that link sound to robot movements or that allocate robots to musical roles. In our system, despite being limited to playing the atomic musical element, i.e., a single note, robots self-organise to play musical creations collectively. We illustrate the modular architecture of our framework by presenting three independent modules that run in parallel to enable the swarm to reach (i) temporal coordination so that robots play in synchrony, (ii) harmonic consensus so that notes are harmonically coherent, and (iii) beat distribution so that notes are distributed throughout time. We implement algorithms for the three modules building upon and extending existing swarm robotics solutions. Our bottom-up and modular approach also enables the use of cheap and accessible robots, hence fostering applicability, scalability, and robustness. Finally, combining the robot’s physical embodiment with the swarm’s plurality brings a unique dimension to the musical performance. We showcase our collaborative music creation framework with simulations and a real robot performance comprising 12 robots. This study shows the potential of combining music with swarm robotics to create musical complexity from simple robotic actions.

Evolutionary mechanisms have always been one of the most popular chapters of Alife. This work adopts an evolutionary perspective and proposes an original algorithm for the construction of genealogical trees of scientific papers on the basis of their citation count evolution in time. The fitness of a paper now amounts to its in-degree growing trend and a “dying” paper will suddenly see this trend declining in time. It will give birth and be taken over by some of its most prevalent citing “offspring”. Practically, this might be used to trace the successive published milestones of a research field. Based on two landmark publications of Alife, we will show of this field has evolved towards more realistic physicochemical simulations and how complex networks, sharing with Alife its multidisplinarity and software grounding, have robbed us the popularity.