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short-paper

Learning to Engage in Interactive Digital Art

Authors:

Dana KulicAuthors Info & Claims

IUI '21: Proceedings of the 26th International Conference on Intelligent User Interfaces

Pages 275 - 279

https://doi.org/10.1145/3397481.3450691

Published: 14 April 2021 Publication History

Abstract

The aim of this study was to determine whether reinforcement learning could increase user engagement in interactive art installations. Building on a physical interactive art installation called The Plants [1] by Playable Streets, reinforcement learning was integrated into a web application adapted from the physical interactive art piece. The original installation consisted of real plants that visitors could touch to produce sounds. A digital model and interface was developed to simulate the physical installation. A user study was conducted with 178 participants. Three modes were examined: the original settings of the installation as designed by the artist; a predetermined fixed schedule of consistently changing sound banks; and a reinforcement learning mode, where an agent changes the interactive behaviours to maximise user engagement. User engagement was estimated by comparing the number of touches by an individual over successive time intervals.

From the trial, it was found that reinforcement learning was able to improve average engagement levels of users by nearly 27%. However, reinforcement learning was not able to increase the average duration users interacted with the installation.

References

[1]

[n.d.]. Playable Streets. https://www.playablestreets.com/the-plants

[2]

Christoph Bartneck, Dana Kulić, Elizabeth Croft, and Susana Zoghbi. 2009. Measurement Instruments for the Anthropomorphism, Animacy, Likeability, Perceived Intelligence, and Perceived Safety of Robots. International Journal of Social Robotics 1, 1 (Jan. 2009), 71–81. https://doi.org/10.1007/s12369-008-0001-3

[3]

Zafer Bilda, Ernest Edmonds, and Linda Candy. 2008. Designing for creative engagement. Design Studies 29, 6 (2008), 525 – 540. https://doi.org/10.1016/j.destud.2008.07.009

[4]

Antonio Camurri and Pasqualino Ferrentino. 1999. Interactive environments for music and multimedia. Multimedia Systems 7, 1 (1999), 32–47. https://doi.org/10.1007/s005300050109 Place: Berlin Heidelberg Publisher: Springer-Verlag.

Digital Library

[5]

Matthew T. K. Chan, Rob Gorbet, Philip Beesley, and Dana Kulic. 2016. Interacting with curious agents: User experience with interactive sculptural systems. In 2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN). IEEE, New York, NY, USA, 151–158. https://doi.org/10.1109/ROMAN.2016.7745104

Digital Library

[6]

Matthew T. K. Chan, Rob Gorbet, Philip Beesley, and Dana Kulič. 2015. Curiosity-Based Learning Algorithm for distributed interactive sculptural systems. In 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 3435–3441. https://doi.org/10.1109/IROS.2015.7353856

Digital Library

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Heriberto Cuayáhuitl, Martijn van Otterlo, Nina Dethlefs, and Lutz Frommberger. 2013. Machine Learning for Interactive Systems and Robots: A Brief Introduction. In Proceedings of the 2nd Workshop on Machine Learning for Interactive Systems: Bridging the Gap Between Perception, Action and Communication (Beijing, China) (MLIS ’13). Association for Computing Machinery, New York, NY, USA, 19–28. https://doi.org/10.1145/2493525.2493530

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T. Degris, P. M. Pilarski, and R. S. Sutton. 2012. Model-Free reinforcement learning with continuous action in practice. In 2012 American Control Conference (ACC). IEEE, Montreal, QC, 2177–2182. https://doi.org/10.1109/ACC.2012.6315022

[9]

Karmen Franinovic and Yon Visell. 2007. New Musical Interfaces in Context: Sonic Interaction Design in the Urban Setting. New York (2007), 6.

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Celine Latulipe, Erin Carroll, and Danielle Lottridge. 2011. Love, hate, arousal and engagement: exploring audience responses to performing arts. In Proceedings of the SIGCHI Conference on human factors in computing systems(CHI ’11). ACM, 1845–1854.

Digital Library

[11]

Lingheng Meng, Daiwei Lin, Adam Francey, Rob Gorbet, Philip Beesley, and Dana Kulić. 2020. Learning to Engage with Interactive Systems: A Field Study on Deep Reinforcement Learning in a Public Museum. J. Hum.-Robot Interact. 10, 1, Article 5 (Oct. 2020), 29 pages. https://doi.org/10.1145/3408876

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Olivier Pietquin and Manuel Lopes. 2014. Machine Learning for Interactive Systems: Challenges and Future Trends. In Workshop Affect, Compagnon Artificiel, Interaction (WACAI 2014). Rouen, France. https://hal.archives-ouvertes.fr/hal-01073947

[13]

Richard S Sutton and Andrew G Barto. 1998. Reinforcement learning an introduction. MIT Press, Cambridge, Mass.

[14]

K. Tsiakas, M. Dagioglou, V. Karkaletsis, and F. Makedon. 2016. Adaptive robot assisted therapy using interactive reinforcement learning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 9979. Springer Verlag, 11–21. https://doi.org/10.1007/978-3-319-47437-3_2 ISSN: 0302-9743.

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Christopher John Cornish Hellaby Watkins. 1989. Learning from Delayed Rewards. Ph.D. Dissertation. King’s College, Cambridge, UK.

Cited By

Kuntjara ALim CCho SPak H(2025)Enhancing Multicultural Visitor Engagement through Digital Art Installations: A Case Study at DPirang, Tongyeong, South KoreaDigital Applications in Archaeology and Cultural Heritage10.1016/j.daach.2025.e00401(e00401)Online publication date: Feb-2025
https://doi.org/10.1016/j.daach.2025.e00401
Batista NMonteiro I(2023)How HCI concepts are used in articles featuring interactive digital arts: a literature review.Proceedings of the XXII Brazilian Symposium on Human Factors in Computing Systems10.1145/3638067.3638116(1-12)Online publication date: 16-Oct-2023
https://dl.acm.org/doi/10.1145/3638067.3638116

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Learning to Engage in Interactive Digital Art

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cover image ACM Conferences

IUI '21: Proceedings of the 26th International Conference on Intelligent User Interfaces

April 2021

618 pages

ISBN:9781450380171

DOI:10.1145/3397481

Copyright © 2021 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 14 April 2021

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IUI '21

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IUI '21: 26th International Conference on Intelligent User Interfaces

April 14 - 17, 2021

TX, College Station, USA

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Overall Acceptance Rate 746 of 2,811 submissions, 27%

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Cited By

Kuntjara ALim CCho SPak H(2025)Enhancing Multicultural Visitor Engagement through Digital Art Installations: A Case Study at DPirang, Tongyeong, South KoreaDigital Applications in Archaeology and Cultural Heritage10.1016/j.daach.2025.e00401(e00401)Online publication date: Feb-2025
https://doi.org/10.1016/j.daach.2025.e00401
Batista NMonteiro I(2023)How HCI concepts are used in articles featuring interactive digital arts: a literature review.Proceedings of the XXII Brazilian Symposium on Human Factors in Computing Systems10.1145/3638067.3638116(1-12)Online publication date: 16-Oct-2023
https://dl.acm.org/doi/10.1145/3638067.3638116

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