Author

Clémence Bergerot

Humboldt-Universität zu BerlinORCID 0000-0001-7640-283XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Neuroscience· 2

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 1 Approach:machine learning (classical)· 1 Organism:rat· 1 Approach:statistical model· 1

Frequent Co-Authors

Alexia DurieziD· 1 shared Boris S GutkiniD· 1 shared Jackson J. ConeiD· 1 shared Mitchell F. RoitmaniD· 1 shared Paweł RomańczukiD· 1 shared Wolfram BarfußiD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

6 top collaborators · 7 mutual co-author links

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1 shared paperNeuroscience

Alexia DuriezORCID

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2 papers

Recent·Most cited

NeurosciencePLoS Computational BiologyPeer-reviewedSep 23, 2026

Deterministic dynamics of distributional multi-agent reinforcement learning

Clémence Bergerot, Paweł Romańczuk, Wolfram Barfuß

This paper develops a computational framework for distributional multi-agent reinforcement learning, showing how optimism, reward discretization, and temporal discounting interact to shape decision-making.

DOI 10.1371/journal.pcbi.1014723

statistical model

𝕏 PostBluesky

NeuroscienceNutrientsPeer-reviewedFeb 17, 2023

Homeostatic Reinforcement Theory Accounts for Sodium Appetitive State- and Taste- Dependent Dopamine Responding.

Alexia Duriez, Clémence Bergerot, Jackson J. Cone…·Boris S Gutkin

This paper extends homeostatic regulation into a reinforcement learning framework to model sodium-seeking behavior and dopamine signaling in rats.

11 citations

ratmachine learning (classical)

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