Sound Swarm: A Synthetic Ecology of Embodied Mesh Synthesizers for Emergent Soundscapes

Mikhail Mansion; Yasuaki Kakehi

Sound Swarm: A Synthetic Ecology of Embodied Mesh Synthesizers for Emergent Soundscapes
Image credit: Mikhail Mansion; Yasuaki Kakehi

Abstract:

Sound Swarm is an embodied, multi-agent system that functions as a self-organizing mesh synthesizer, generating soundscapes through distributed sensing and environmentally mediated interaction. As these systems scale, traditional musical concepts—individual voice assignment, score-based synchronization, and deterministic event mapping—break down because the acoustic environment introduces propagation delay, masking, reflections, and spatial heterogeneity. We argue that composing for such systems requires a shift from event-specification to condition-setting: designing interaction rules, constraints, spatial arrangements, and time-scales under which sonic organization can emerge. This paper details a three-tier architecture—Perception, Behavior, and Expression—that decouples real-time audio synthesis from low-rate “colony cognition.” We introduce a graph-based method for collective spatial sense-making: pairwise RF/acoustic measurements populate a relational tensor which is interpreted by a lightweight neural relational model to infer topology in situ. The framework is grounded in a biological taxonomy of coordination behaviors: honeybee-inspired role election for hierarchy, ant-inspired stigmergy for environmental coupling, and tree frog models for rhythmic coordination. By treating the swarm as a synthetic ecology, we demonstrate how emergent musical form arises from the triadic interaction between user-defined conditions, the physical environment, and agent-level biological heuristics.