Perreault, D., Audry, S., Cusson, V., Drouin, D., & Drouin Trempe, V. (2025). From performance to installation: How interactive reinforcement learning reframes the roles of performers and audiences. In Proceedings of the International Conference on New Interfaces for Musical Expression (NIME – New Interfaces for Musical Expression 2025).
This article explores how artificial intelligence, and more specifically Interactive Reinforcement Learning (IRL), is transforming the traditional roles of artists and audiences in immersive audiovisual performances. By adapting a musical co-creation tool (Co-Explorer) to new contexts, the researchers highlight three emerging figures of the performer: the designer, the guide, and the machine-performer.
The study reveals how IRL opens the door to collective creation, where the audience itself can influence the artwork in real time through its interactions. This approach also raises concrete challenges, particularly regarding the temporality of the works and their presentation in exhibition contexts.
This work is part of a broader reflection on co-creation systems and hybrid ecosystems that bring together artists, machines, and audiences.
Publication link: https://nime.org/proceedings/2025/nime2025_76.pdf (plug-ins)
