The following abstracts accompany a series of workshops presented at conferences over the course of the project.
Plant, N., Hilton, C., Fiebrink, R., Gillies, M., Gonzalez Diaz, C., Gibson, R., Hilton, C., Martelli, M., Perry, P., and Zbyszyński, M. (2021) Interactive Machine Learning for Embodied Interaction Design: A tool and methodology. In Proceedings of the Fifteenth International Conference on Tangible, Embedded, and Embodied Interaction (TEI ’21). Association for Computing Machinery, New York, USA, Article 68, 1–5.
Plant, N., Fiebrink, R., Gillies, M., Gonzalez Diaz, C., Gibson, R., Hilton, C., Martelli, M., Perry, P., and Zbyszyński, M. (2020) Movement interaction design for immersive media using interactive machine learning. In MOCO ’20: Proceedings of the 7th International Conference on Movement and Computing
Plant, N., Fiebrink, R., Gillies, M., Gonzalez Diaz, C., Gibson, R., Hilton, C., Martelli, M., Perry, P., and Zbyszyński, M. (2020) Using Machine Learning to Design Movement Interaction in VR. In Proceedings of EVA London 2020: Electronic Visualisation & the Arts.
This paper, published before the start of the project, lays out some of the practical and theoretical foundations of our research.
Gillies, Marco. 2019. Understanding the role of Interactive Machine Learning in Movement Interaction Design. ACM Transactions on Computer-Human Interaction, 26(1), ISSN 1073-0516
This short paper introduces interact as an interactive machine learning unity plugin.
Gonzalez Diaz, C., Perry, P., & Fiebrink, R. 2019. Interactive Machine Learning for More Expressive Game Interactions. Proceedings of the IEEE Conference on Games. London, UK.