Towards an Experimentation Platform for Hybrid Human-AI Sequential Decision-Making
Publication date
2025-09-22
Authors
Aydın, Hüseyin
Godin-Dubois, Kevin
Goncalvez Braz, Libio
Den Hengst, Floris
Baraka, Kim
Çelikok, Mustafa Mert
Sauter, Andreas
Wang, Shihan
Oliehoek, Frans A.
Editors
Pedreschi, Dino
Milano, Michela
Tiddi, Ilaria
Russell, Stuart
Boldrini, Chiara
Pappalardo, Luca
Passerini, Andrea
Wang, Shenghui
Advisors
Supervisors
Document Type
Part of book
Metadata
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License
cc_by_nc
Abstract
We present SHARPIE (Shared Human-AI Reinforcement Learning Platform for Interactive Experiments), a generic framework to support experiments with RL agents and humans. It consists of a versatile wrapper for RL environments and algorithm libraries, a participant-facing web interface, logging utilities, and deployment on popular cloud and participant recruitment platforms. It empowers researchers to study a wide variety of research questions related to the interaction between humans and RL agents and aims to standardize the field of study on RL in human contexts.
Keywords
experimentation, hybrid AI, reinforcement learning, software, Artificial Intelligence
Citation
Aydin, H, Godin-Dubois, K, Goncalvez Braz, L, Den Hengst, F, Baraka, K, Çelikok, M M, Sauter, A, Wang, S & Oliehoek, F A 2025, Towards an Experimentation Platform for Hybrid Human-AI Sequential Decision-Making. in D Pedreschi, M Milano, I Tiddi, S Russell, C Boldrini, L Pappalardo, A Passerini & S Wang (eds), HHAI 2025 - Proceedings of the 4th International Conference on Hybrid Human-Artificial Intelligence. Frontiers in Artificial Intelligence and Applications, vol. 408, IOS Press BV, pp. 486-488, 4th International Conference on Hybrid Human-Artificial Intelligence, HHAI 2025, Pisa, Italy, 9/06/25. https://doi.org/10.3233/FAIA250669, conference