Skip to content
Free planNo credit card requiredStart writing
AI for Research home
AI for Research home
Dashboard
Sign inGet started

preprint · ArXiv.org · 2025

Model selection for behavioral learning data and applications to contextual bandits

Julien Aubert, Louis Köhler, Luc Lehéricy, Giulia Mezzadri, Patricia Reynaud-Bouret

Cited by 0Open access

Abstract

Learning for animals or humans is the process that leads to behaviors better adapted to the environment. This process highly depends on the individual that learns and is usually observed only through the individual's actions. This article presents ways to use this individual behavioral data to find the model that best explains how the individual learns. We propose two model selection methods: a general hold-out procedure and an AIC-type criterion, both adapted to non-stationary dependent data. We provide theoretical error bounds for these methods that are close to those of the standard i.i.d. case. To compare these approaches, we apply them to contextual bandit models and illustrate their use on both synthetic and experimental learning data in a human categorization task.

Cite this paper

APA 7

Aubert, J., Köhler, L., Lehéricy, L., Mezzadri, G., & Reynaud-Bouret, P. (2025). Model selection for behavioral learning data and applications to contextual bandits. ArXiv.org.

MLA 9

Aubert, Julien, et al. “Model selection for behavioral learning data and applications to contextual bandits.” ArXiv.org, 2025.

Chicago

Aubert, Julien, Louis Köhler, Luc Lehéricy, Giulia Mezzadri, and Patricia Reynaud-Bouret. 2025. “Model selection for behavioral learning data and applications to contextual bandits.” ArXiv.org.

Harvard

Aubert, J. et al. (2025) ‘Model selection for behavioral learning data and applications to contextual bandits’, ArXiv.org.

BibTeX
@misc{aubert2025model,
  title = {{Model selection for behavioral learning data and applications to contextual bandits}},
  author = {Aubert, Julien and Köhler, Louis and Lehéricy, Luc and Mezzadri, Giulia and Reynaud-Bouret, Patricia},
  journal = {ArXiv.org},
  year = {2025}
}

Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.

Related papers