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The Animal-AI Environment: A virtual laboratory for comparative cognition and artificial intelligence research

Voudouris, Konstantinos; Slater, Ben; Cheke, Lucy G.; Schellaert, Wout; Hernández-Orallo, José; Halina, Marta; Patel, Matishalin; Alhas, Ibrahim; Mecattaf, Matteo G.; Burden, John; Holmes, Joel; Chaubey, Niharika; Donnelly, Niall; Crosby, Matthew

Authors

Konstantinos Voudouris

Ben Slater

Lucy G. Cheke

Wout Schellaert

José Hernández-Orallo

Marta Halina

Ibrahim Alhas

Matteo G. Mecattaf

John Burden

Joel Holmes

Niharika Chaubey

Niall Donnelly

Matthew Crosby



Abstract

The Animal-AI Environment is a unique game-based research platform designed to facilitate collaboration between the artificial intelligence and comparative cognition research communities. In this paper, we present the latest version of the Animal-AI Environment, outlining several major features that make the game more engaging for humans and more complex for AI systems. These features include interactive buttons, reward dispensers, and player notifications, as well as an overhaul of the environment’s graphics and processing for significant improvements in agent training time and quality of the human player experience. We provide detailed guidance on how to build computational and behavioural experiments with the Animal-AI Environment. We present results from a series of agents, including the state-of-the-art deep reinforcement learning agent Dreamer-v3, on newly designed tests and the Animal-AI testbed of 900 tasks inspired by research in the field of comparative cognition. The Animal-AI Environment offers a new approach for modelling cognition in humans and non-human animals, and for building biologically inspired artificial intelligence.

Citation

Voudouris, K., Slater, B., Cheke, L. G., Schellaert, W., Hernández-Orallo, J., Halina, M., Patel, M., Alhas, I., Mecattaf, M. G., Burden, J., Holmes, J., Chaubey, N., Donnelly, N., & Crosby, M. (in press). The Animal-AI Environment: A virtual laboratory for comparative cognition and artificial intelligence research. Behavior research methods, 57(4), Article 107. https://doi.org/10.3758/s13428-025-02616-3

Journal Article Type Article
Acceptance Date Jan 19, 2025
Online Publication Date Feb 28, 2025
Deposit Date Mar 3, 2025
Publicly Available Date Mar 4, 2025
Journal Behavior Research Methods
Print ISSN 1554-351X
Publisher Springer Verlag
Peer Reviewed Peer Reviewed
Volume 57
Issue 4
Article Number 107
DOI https://doi.org/10.3758/s13428-025-02616-3
Public URL https://hull-repository.worktribe.com/output/5073703

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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0

Copyright Statement
© The Author(s) 2025.
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.




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