This research focuses on the expanded notion of the “digital instrument” in light of the radically different nature of computational processes, with their ability to extend performance action beyond immediate action/sound couplings. This work integrates machine learning and distributed performance databases to include control of temporal processes on multiple scales, with elements of creative agency afforded to instrumental systems. Foundational projects that inform this work include the GREIS instrumental performance system.

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