Abstract
Studies of human exploration frequently cast people as serendipitously stumbling upon good options. Yet these studies may not capture the richness of exploration strategies that people exhibit in more complex environments. Here we study behaviour in a large dataset of 29,493 players of the richly structured online game ‘Little Alchemy 2’. In this game, players start with four elements, which they can combine to create up to 720 complex objects. We find that players are driven not only by external reward signals, such as an attempt to produce successful outcomes, but also by an intrinsic motivation to create objects that empower them to create even more objects. We find that this drive for empowerment is eliminated when playing a game variant that lacks recognizable semantics, indicating that people use their knowledge about the world and its possibilities to guide their exploration. Our results suggest that the drive for empowerment may be a potent source of intrinsic motivation in richly structured domains, particularly those that lack explicit reward signals.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$119.00 per year
only $9.92 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Data availability
Anonymized participant data of the experiments and model simulation data are available at https://github.com/franziskabraendle/alchemy_empowerment (ref. 32). Third party data of participants playing the original game may be shared upon reasonable request (franziska.braendle@tuebingen.mpg.de).
Code availability
The code used for all experiments, models and analyses is available at https://github.com/franziskabraendle/alchemy_empowerment (ref. 32).
References
Schulz, E. & Gershman, S. J. The algorithmic architecture of exploration in the human brain. Curr. Opin. Neurobiol. 55, 7–14 (2019).
Wilson, R. C., Bonawitz, E., Costa, V. D. & Ebitz, R. B. Balancing exploration and exploitation with information and randomization. Curr. Opin. Behav. Sci. 38, 49–56 (2021).
Daw, N. D., O’Doherty, J. P., Dayan, P., Seymour, B. & Dolan, R. J. Cortical substrates for exploratory decisions in humans. Nature 441, 876–879 (2006).
Wilson, R. C., Geana, A., White, J. M., Ludvig, E. A. & Cohen, J. D. Humans use directed and random exploration to solve the explore–exploit dilemma. J. Exp. Psychol. Gen. 143, 155–164 (2014).
Speekenbrink, M. & Konstantinidis, E. Uncertainty and exploration in a restless bandit problem. Top. Cogn. Sci. 7, 351–367 (2015).
Gershman, S. J. Deconstructing the human algorithms for exploration. Cognition 173, 34–42 (2018).
Gershman, S. Uncertainty and exploration. Decision 6, 277–286 (2019).
Brändle, F., Binz, M. & Schulz, E. in The Drive for Knowledge (eds Cogliati Dezza, I. et al) Ch. 7 (Cambridge Univ. Press, 2022).
Chu, J. & Schulz, L. Not playing by the rules: exploratory play, rational action, and efficient search. Open Mind 7, 294–317 (2023).
Gottlieb, J., Oudeyer, P.-Y., Lopes, M. & Baranes, A. Information-seeking, curiosity, and attention: computational and neural mechanisms. Trends Cogn. Sci. 17, 585–593 (2013).
Payzan-LeNestour, E. & Bossaerts, P. Risk, unexpected uncertainty, and estimation uncertainty: Bayesian learning in unstable settings. PLoS Comput. Biol. 7, e1001048 (2011).
Knox, W. B., Otto, A. R., Stone, P. & Love, B. C. The nature of belief-directed exploratory choice in human decision-making. Front. Psychol. https://doi.org/10.3389/fpsyg.2011.00398 (2012).
Schulz, E., Wu, C. M., Ruggeri, A. & Meder, B. Searching for rewards like a child means less generalization and more directed exploration. Psychol. Sci. 30, 1561–1572 (2019).
Little Alchemy 2. Google Play https://play.google.com/store/apps/details?id=com.recloak.littlealchemy2 (2021).
Jiang, M. et al. Wordcraft: an environment for benchmarking commonsense agents. Preprint at arXiv https://doi.org/10.48550/arXiv.2007.09185 (2020).
Schulz, E., Franklin, N. T. & Gershman, S. J. Finding structure in multi-armed bandits. Cogn. Psychol. 119, 101261 (2020).
Schulz, E. et al. Structured, uncertainty-driven exploration in real-world consumer choice. Proc. Natl Acad. Sci. USA 116, 13903–13908 (2019).
Klyubin, A. S., Polani, D. & Nehaniv, C. L. All else being equal be empowered. In Proc. 8th European Conference on Advances in Artificial Life (eds Capcarrère, M.S. et al) 744–753 (Springer-Verlag, Berlin, 2005).
Colantonio, J. & Bonawitz, E. Awesome play: awe increases preschooler’s exploration and discovery. In Proc. 40th Annual Conference of the Cognitive Science Society (eds Kalish, C. et al.) 1536–1541 (Cognitive Science Society, Seattle, 2018).
Salge, C., Glackin, C. & Polani, D. in Guided Self-Organization: Inception (ed. Prokopenko, M.) 67–114 (Springer, 2014).
Daw, N. D., Gershman, S. J., Seymour, B., Dayan, P. & Dolan, R. J. Model-based influences on humans’ choices and striatal prediction errors. Neuron 69, 1204–1215 (2011).
Joulin, A. et al. Fasttext. zip: compressing text classification models. Preprint at arXiv https://doi.org/10.48550/arXiv.1612.03651 (2016).
Bhatia, S. Associative judgment and vector space semantics. Psychol. Rev. 124, 1–20 (2017).
Fründ, I., Wichmann, F. A. & Macke, J. H. Quantifying the effect of intertrial dependence on perceptual decisions. J. Vis. https://doi.org/10.1167/14.7.9 (2014).
Schmidhuber, J. Powerplay: training an increasingly general problem solver by continually searching for the simplest still unsolvable problem. Front. Psychol. 4, 313 (2013).
Nasiriany, S., Pong, V. H., Lin, S. & Levine, S. Planning with goal-conditioned policies. In Advances in Neural Information Processing Systems 32 (NeurIPS 2019) (eds Wallach, H. et al.) 14843–14854 (Neural Information Processing Systems Foundation, San Diego, 2019).
Campero, A. et al. Learning with AMIGo: adversarially motivated intrinsic goals. Preprint at arXiv https://doi.org/10.48550/arXiv.2006.12122 (2020).
Chitnis, R., Silver, T., Tenenbaum, J., Kaelbling, L. P. & Lozano-Perez, T. GLIB: efficient exploration for relational model-based reinforcement learning via goal-literal babbling. Preprint at arXiv https://doi.org/10.48550/arXiv.2001.08299 (2020).
Pathak, D., Gandhi, D. & Gupta, A. Self-supervised exploration via disagreement. In Proc. 36th International Conference on Machine Learning (eds Chaudhuri, K. & Salakhutdinov, R.) 5062–5071 (PMLR, Cambridge, MA, 2019).
Gottlieb, J. & Oudeyer, P.-Y. Towards a neuroscience of active sampling and curiosity. Nat. Rev. Neurosci. 19, 758–770 (2018).
Chu, J. & Schulz, L. E. Play, curiosity, and cognition. Annu. Rev. Dev. Psychol. 2, 317–343 (2020).
Brändle, F., Stocks, L. J. & Schulz, E. franziskabraendle/alchemy_empowerment. Zenodo https://doi.org/10.5281/zenodo.8010316 (2023).
Acknowledgements
We thank J. Koziol for the ‘Little Alchemy 2’ dataset. This work was supported by the Max Planck Society, the Volkswagen Foundation (VW98569, E.S.) and a Jacobs Research Fellowship (E.S.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the paper.
Author information
Authors and Affiliations
Contributions
F.B., L.J.S., S.J.G. and E.S. conceived the study. F.B. and E.S. collected the data. F.B., L.J.S. and E.S. performed the analyses. F.B., L.J.S., J.B.T., S.J.G. and E.S. wrote the paper.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Peer review
Peer review information
Nature Human Behaviour thanks Kou Murayama and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Supplementary Information
Supplementary information and Supplementary Figs 1–6 and Tables 1–10.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Brändle, F., Stocks, L.J., Tenenbaum, J.B. et al. Empowerment contributes to exploration behaviour in a creative video game. Nat Hum Behav 7, 1481–1489 (2023). https://doi.org/10.1038/s41562-023-01661-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41562-023-01661-2